NLP4News_Tutorial.ipynb

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  "metadata": {
    "colab": {
      "name": "NLP$News_Tutorial.ipynb",
      "provenance": [],
      "collapsed_sections": []
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "code",
      "metadata": {
        "id": "oHYv2kzyrc1v"
      },
      "source": [
        "!pip install bertopic"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MUr_iBisGBm6"
      },
      "source": [
        "!pip install bert-extractive-summarizer"
      ],
      "execution_count": null,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "W2AENOWyt9H-"
      },
      "source": [
        "## 1. File Configuration\n",
        "By running the following window you can upload the ulits.py, and NLP4News.py libraries, as well as any dataset.\n",
        "\n",
        "This is done in order to access them in the notebook"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "resources": {
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              "ok": true,
              "headers": [
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                  "content-type",
                  "application/javascript"
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              "status": 200,
              "status_text": ""
            }
          },
          "base_uri": "https://localhost:8080/",
          "height": 111
        },
        "id": "7HVUslBdsatN",
        "outputId": "75252a63-0c57-4a62-ecb1-7ef38985c0f0"
      },
      "source": [
        "from google.colab import files\n",
        "files.upload()"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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              "     <output id=\"result-23c33a57-d3d6-4e67-bd4c-8ff6402e437b\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
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          "metadata": {
            "tags": []
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        {
          "output_type": "stream",
          "text": [
            "Saving NLP4News.py to NLP4News.py\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "{'NLP4News.py': b'# from CS4490Z_Thesis.utils import testing_script\\r\\nfrom utils import MyDataset,Preprocess\\r\\nimport gensim.corpora as corpora\\r\\nimport gensim\\r\\nfrom sklearn.feature_extraction.text import CountVectorizer\\r\\nfrom sklearn.decomposition import LatentDirichletAllocation\\r\\nfrom sklearn.model_selection import GridSearchCV\\r\\nimport pandas as pd\\r\\nfrom matplotlib import pyplot as plt\\r\\nfrom wordcloud import WordCloud, STOPWORDS\\r\\nimport matplotlib.colors as mcolors\\r\\nimport seaborn as sns\\r\\nimport numpy as np\\r\\nfrom sklearn.manifold import TSNE\\r\\nfrom bokeh.plotting import figure, output_file, show\\r\\nfrom bokeh.models import Label\\r\\nfrom bokeh.io import output_notebook\\r\\nfrom matplotlib.patches import Rectangle\\r\\nfrom bertopic import BERTopic\\r\\nfrom nltk.corpus import stopwords\\r\\nfrom nltk.sentiment import SentimentIntensityAnalyzer\\r\\nfrom summarizer import Summarizer\\r\\nimport nltk\\r\\n\\r\\nclass LDA_Topic_Model:\\r\\n\\r\\n    def __init__(self, df, n_comp =[4, 5, 6, 7, 8], ld = [.5, .7, .9] ):\\r\\n\\r\\n        self.data = df\\r\\n\\r\\n        print(\\'Beginning vecorization\\')\\r\\n        vectorizer = CountVectorizer(analyzer=\\'word\\',       \\r\\n                             min_df=10,                        # minimum reqd occurences of a word \\r\\n                             stop_words=\\'english\\',             # remove stop words\\r\\n                             lowercase=True,                   # convert all words to lowercase\\r\\n                             token_pattern=\\'[a-zA-Z0-9]{3,}\\',  # num chars > 3\\r\\n                             # max_features=50000,             # max number of uniq words\\r\\n                            )\\r\\n\\r\\n        self.data_vectorized = vectorizer.fit_transform(Preprocess.lemmatize(df))\\r\\n\\r\\n        print(\\'Vecorization complete\\')\\r\\n\\r\\n        search_params = {\\'n_components\\': n_comp, \\'learning_decay\\': ld}\\r\\n\\r\\n        # Init the Model\\r\\n        lda = LatentDirichletAllocation()\\r\\n\\r\\n        print(\\'Beginning grid search\\')\\r\\n\\r\\n        # Init Grid Search Class\\r\\n        self.gs_model = GridSearchCV(lda, param_grid=search_params)\\r\\n\\r\\n        # Do the Grid Search\\r\\n        self.gs_model.fit(self.data_vectorized)\\r\\n        self.best_lda_model = self.gs_model.best_params_\\r\\n        print(\\'Completed grid search\\')\\r\\n\\r\\n        self.dict = corpora.Dictionary(df)\\r\\n        self.corpus = [self.dict.doc2bow(text) for text in df]\\r\\n\\r\\n        print(\\'Constructing LDA\\')\\r\\n\\r\\n        self.model = gensim.models.ldamodel.LdaModel(corpus=self.corpus, id2word=self.dict,\\r\\n            num_topics=self.gs_model.best_params_[\\'n_components\\'], random_state=100, update_every=1, chunksize=10, passes=10, \\r\\n            alpha=\\'symmetric\\', iterations=100, per_word_topics=True)\\r\\n        print(\\'Competed LDA\\')\\r\\n\\r\\n        # topics = self.model.print_topics(num_words = 20)\\r\\n        # for i in topics: print(i)\\r\\n\\r\\n    def get_dominant_topics(self):\\r\\n\\r\\n        sent_topics_df = pd.DataFrame()\\r\\n\\r\\n        # Get main topic in each document\\r\\n        for i, row_list in enumerate(self.model[self.corpus]):\\r\\n            row = row_list[0] if self.model.per_word_topics else row_list            \\r\\n            # print(row)\\r\\n            row = sorted(row, key=lambda x: (x[1]), reverse=True)\\r\\n            # Get the Dominant topic, Perc Contribution and Keywords for each document\\r\\n            for j, (topic_num, prop_topic) in enumerate(row):\\r\\n                if j == 0:  # => dominant topic\\r\\n                    wp = self.model.show_topic(topic_num)\\r\\n                    topic_keywords = \", \".join([word for word, prop in wp])\\r\\n                    sent_topics_df = sent_topics_df.append(pd.Series([int(topic_num), round(prop_topic,4), topic_keywords]), ignore_index=True)\\r\\n                else:\\r\\n                    break\\r\\n        sent_topics_df.columns = [\\'Dominant_Topic\\', \\'Perc_Contribution\\', \\'Topic_Keywords\\']\\r\\n\\r\\n        # Add original text to the end of the output\\r\\n        contents = pd.Series(self.data)\\r\\n        df_topic_sents_keywords = pd.concat([sent_topics_df, contents], axis=1)\\r\\n\\r\\n        # Format\\r\\n        df_dominant_topic = df_topic_sents_keywords.reset_index()\\r\\n        df_dominant_topic.columns = [\\'Document_No\\', \\'Dominant_Topic\\', \\'Topic_Perc_Contrib\\', \\'Keywords\\', \\'Text\\']\\r\\n\\r\\n        return df_dominant_topic\\r\\n\\r\\n    def get_topic_word_cloud(self, topic_id):\\r\\n\\r\\n        cols = [color for name, color in mcolors.TABLEAU_COLORS.items()]\\r\\n\\r\\n        topics = self.model.show_topics(formatted=False)\\r\\n\\r\\n        stop_words = stopwords.words(\\'english\\')\\r\\n        stop_words.extend([\\'from\\', \\'subject\\', \\'re\\', \\'edu\\', \\'use\\', \\'not\\', \\'would\\', \\'say\\', \\'could\\', \\'_\\', \\'be\\', \\'know\\', \\'good\\', \\'go\\', \\'get\\', \\'do\\', \\'done\\', \\'try\\', \\'many\\', \\'some\\', \\'nice\\', \\'thank\\', \\'think\\', \\'see\\', \\'rather\\', \\'easy\\', \\'easily\\', \\'lot\\', \\'lack\\', \\'make\\', \\'want\\', \\'seem\\', \\'run\\', \\'need\\', \\'even\\', \\'right\\', \\'line\\', \\'even\\', \\'also\\', \\'may\\', \\'take\\', \\'come\\'])\\r\\n\\r\\n\\r\\n        cloud = WordCloud(stopwords=stop_words,\\r\\n                  background_color=\\'white\\',\\r\\n                  width=2500,\\r\\n                  height=1800,\\r\\n                  max_words=10,\\r\\n                  colormap=\\'tab10\\',\\r\\n                  color_func=lambda *args, **kwargs: cols[topic_id],\\r\\n                  prefer_horizontal=1.0)\\r\\n\\r\\n        plt.figure(figsize=(10,10))\\r\\n        topic_words = dict(topics[topic_id][1])\\r\\n        cloud.generate_from_frequencies(topic_words, max_font_size=300)\\r\\n        plt.gca().imshow(cloud)\\r\\n        plt.gca().set_title(\\'Topic \\' + str(topic_id), fontdict=dict(size=16))\\r\\n        plt.gca().axis(\\'off\\')\\r\\n        plt.savefig(f\\'topic_{topic_id}_word_cloud.jpeg\\')\\r\\n\\r\\n    def get_topic_word_dist(self, topic_id):\\r\\n\\r\\n        cols = [color for name, color in mcolors.TABLEAU_COLORS.items()]\\r\\n\\r\\n        df_dominant_topic = self.get_dominant_topics()\\r\\n\\r\\n        plt.figure(figsize=(10,10))\\r\\n        df_dominant_topic_sub = df_dominant_topic.loc[df_dominant_topic.Dominant_Topic == topic_id, :]\\r\\n        doc_lens = [len(d) for d in df_dominant_topic_sub.Text]\\r\\n        plt.hist(doc_lens, bins = 1000, color=cols[topic_id])\\r\\n        plt.title(label=f\\'Document Word Count for Topic {topic_id}\\')\\r\\n        plt.ylabel(\\'Number of Documents\\')\\r\\n        plt.savefig(f\\'topic_{topic_id}_word_distribution.jpeg\\')\\r\\n\\r\\n    def get_sentence_colors(self, start, end):\\r\\n\\r\\n        corp = self.corpus[start:end]\\r\\n        mycolors = [color for name, color in mcolors.TABLEAU_COLORS.items()]\\r\\n\\r\\n        fig, axes = plt.subplots(end-start, 1, figsize=(20, (end-start)*0.95), dpi=160)\\r\\n                                \\r\\n        axes[0].axis(\\'off\\')\\r\\n        for i, ax in enumerate(axes):\\r\\n            if i > 0:\\r\\n                corp_cur = corp[i-1] \\r\\n                topic_percs, wordid_topics, wordid_phivalues = self.model[corp_cur]\\r\\n                word_dominanttopic = [(self.model.id2word[wd], topic[0]) for wd, topic in wordid_topics]    \\r\\n                ax.text(0.01, 0.5, \"Doc \" + str(i-1) + \": \", verticalalignment=\\'center\\',\\r\\n                        fontsize=16, color=\\'black\\', transform=ax.transAxes, fontweight=700)\\r\\n\\r\\n                # Draw Rectange\\r\\n                topic_percs_sorted = sorted(topic_percs, key=lambda x: (x[1]), reverse=True)\\r\\n                ax.add_patch(Rectangle((0.0, 0.05), 0.99, 0.90, fill=None, alpha=1, \\r\\n                                        color=mycolors[topic_percs_sorted[0][0]], linewidth=2))\\r\\n\\r\\n                word_pos = 0.06\\r\\n                for j, (word, topics) in enumerate(word_dominanttopic):\\r\\n                    if j < 14:\\r\\n                        ax.text(word_pos, 0.5, word,\\r\\n                                horizontalalignment=\\'left\\',\\r\\n                                verticalalignment=\\'center\\',\\r\\n                                fontsize=16, color=mycolors[topics],\\r\\n                                transform=ax.transAxes, fontweight=700)\\r\\n                        word_pos += .009 * len(word)  # to move the word for the next iter\\r\\n                        ax.axis(\\'off\\')\\r\\n                ax.text(word_pos, 0.5, \\'. . .\\',\\r\\n                        horizontalalignment=\\'left\\',\\r\\n                        verticalalignment=\\'center\\',\\r\\n                        fontsize=16, color=\\'black\\',\\r\\n                        transform=ax.transAxes)       \\r\\n\\r\\n        plt.subplots_adjust(wspace=0, hspace=0)\\r\\n        plt.suptitle(\\'Sentence Topic Coloring for Documents: \\' + str(start) + \\' to \\' + str(end-2), fontsize=22, y=0.95, fontweight=700)\\r\\n        plt.tight_layout()\\r\\n        plt.show() \\r\\n        plt.savefig(f\\'word_and_article_{start}_{end}.png\\')\\r\\n\\r\\n    def get_sne_cluster(self):\\r\\n\\r\\n        # Get topic weights\\r\\n        topic_weights = []\\r\\n        for i, row_list in enumerate(self.model[self.corpus]):\\r\\n            topic_weights.append([w for i, w in row_list[0]])\\r\\n\\r\\n        # Array of topic weights    \\r\\n        arr = pd.DataFrame(topic_weights).fillna(0).values\\r\\n\\r\\n        # Keep the well separated points (optional)\\r\\n        arr = arr[np.amax(arr, axis=1) > 0.35]\\r\\n\\r\\n        # Dominant topic number in each doc\\r\\n        topic_num = np.argmax(arr, axis=1)\\r\\n\\r\\n        # tSNE Dimension Reduction\\r\\n        tsne_model = TSNE(n_components=2, verbose=1, random_state=0, angle=.99, init=\\'pca\\')\\r\\n        tsne_lda = tsne_model.fit_transform(arr)\\r\\n\\r\\n        # Plot the Topic Clusters using Bokeh\\r\\n        output_notebook()\\r\\n        n_topics = 4\\r\\n        mycolors = np.array([color for name, color in mcolors.TABLEAU_COLORS.items()])\\r\\n        plot = figure(title=\"t-SNE Clustering of {} LDA Topics\".format(n_topics), \\r\\n                    plot_width=900, plot_height=700)\\r\\n        plot.scatter(x=tsne_lda[:,0], y=tsne_lda[:,1], color=mycolors[topic_num])\\r\\n        show(plot)\\r\\n        plt.savefig(f\\'t_sne_clustering_lda.png\\')\\r\\n\\r\\nclass BERT_topic_Model:\\r\\n\\r\\n    def __init__(self, texts, dates):\\r\\n\\r\\n        self.articles =  texts\\r\\n        self.dates = dates\\r\\n        self.model = BERTopic()\\r\\n        self.topics, _ = self.model.fit_transform(self.articles)\\r\\n\\r\\n    def get_num_topics(self):\\r\\n\\r\\n        return len(self.model.get_topic_info())\\r\\n\\r\\n    def get_topic_desc(self):\\r\\n\\r\\n        return (self.model.get_topic_info())\\r\\n\\r\\n    def show_topic_clusters(self):\\r\\n\\r\\n        self.model.visualize_topics()\\r\\n\\r\\n    def show_dynamic_topic_plots(self, num_topics):\\r\\n\\r\\n        topics_over_time = self.model.topics_over_time(self.articles, self.topics, self.dates, nr_bins=20)\\r\\n        self.model.visualize_topics_over_time(topics_over_time, top_n_topics=num_topics)\\r\\n\\r\\n    def get_topic_table(self):\\r\\n\\r\\n        self.topic_matrix = pd.DataFrame(0, index=np.arange(len(self.articles)), columns=[\\'Topic 1\\',\\'Topic 2\\', \\'Topic 3\\', \\'Topic 4\\',\\'Topic 5\\'])\\r\\n\\r\\n        for idx, i in enumerate(self.articles):\\r\\n\\r\\n            # if (idx % 100) == 0: print(f\\'{idx} topics classified\\')\\r\\n            \\r\\n            topic_list = self.model.find_topics(i)[0]\\r\\n            # print(topic_list)\\r\\n\\r\\n            self.topic_matrix[\\'Topic 1\\'][idx] = topic_list[0]\\r\\n            self.topic_matrix[\\'Topic 2\\'][idx] = topic_list[1]\\r\\n            self.topic_matrix[\\'Topic 3\\'][idx] = topic_list[2]\\r\\n            self.topic_matrix[\\'Topic 4\\'][idx] = topic_list[3]\\r\\n            self.topic_matrix[\\'Topic 5\\'][idx] = topic_list[4]\\r\\n            # self.model.head()\\r\\n\\r\\n        return self.topic_matrix\\r\\n\\r\\nclass VADER_sentiment_analyzer:\\r\\n\\r\\n    def __init__(self, texts):\\r\\n\\r\\n        nltk.download([\"names\",\"stopwords\",\"state_union\",\"averaged_perceptron_tagger\",\"vader_lexicon\",\"punkt\"])\\r\\n\\r\\n        self.articles = texts\\r\\n        self.polarity =  [0] * len(texts)\\r\\n\\r\\n        sia = SentimentIntensityAnalyzer()\\r\\n\\r\\n        for idx, i in enumerate(texts):\\r\\n\\r\\n            self.polarity[idx] += sia.polarity_scores(str(i))[\\'compound\\']\\r\\n\\r\\n        self.polarity_matrix = pd.DataFrame(self.polarity, columns=[\\'Polarity\\'])\\r\\n\\r\\n    def get_text_polarity(self):\\r\\n\\r\\n        return self.polarity_matrix\\r\\n\\r\\nclass BERT_Summarization_Model:\\r\\n\\r\\n    def __init__(self, texts):\\r\\n\\r\\n        self.model = Summarizer()\\r\\n        self.data = texts\\r\\n\\r\\n        # abstracts = [\\'\\'] * len(texts)\\r\\n\\r\\n        # for idx, i in enumerate(texts):\\r\\n\\r\\n        #     abstracts[idx] = self.model(i, num_sentences = 3)\\r\\n\\r\\n        # self.summs = pd.DataFrame(abstracts, columns=[\\'Summarizations\\'])\\r\\n\\r\\n    def get_spec_text_sum(self, text_id, n_sentences):\\r\\n\\r\\n        try:\\r\\n            \\r\\n            return self.model(self.data[text_id], num_sentences = n_sentences)\\r\\n\\r\\n        except:\\r\\n\\r\\n            return -1\\r\\n\\r\\nclass NLP_Controller:\\r\\n\\r\\n    def __init__(self,file_name):\\r\\n\\r\\n        self.df = MyDataset(file_name)\\r\\n        # self.size = len(self.df.dataset[\\'Heading\\'])\\r\\n\\r\\n    def tm_bert(self):\\r\\n\\r\\n        articles, dates = self.df.preprocess_for_bert()\\r\\n        return BERT_topic_Model(articles, dates) \\r\\n\\r\\n    def tm_lda(self):\\r\\n\\r\\n        return LDA_Topic_Model(self.df.preprocess_for_LDA())\\r\\n\\r\\n    def sa_vader(self):\\r\\n\\r\\n        # return VADER_sentiment_analyzer(self.df.preprocess_for_bert())\\r\\n        return VADER_sentiment_analyzer(self.df.dataset.Heading)\\r\\n        # print(self.df.dataset.Heading)\\r\\n    \\r\\n    def sum_bert(self):\\r\\n\\r\\n        # articles, _ = self.df.preprocess_for_bert()\\r\\n        articles = self.df.dataset.Article\\r\\n        return BERT_Summarization_Model(articles)\\r\\n\\r\\n    def get_dataset(self):\\r\\n\\r\\n        return self.df\\r\\n\\r\\n    def get_full_table(self,topic_model, polarity_model):\\r\\n\\r\\n        self.df.dataset.reset_index(drop=True, inplace=True)\\r\\n\\r\\n        polarity_matrix = polarity_model.get_text_polarity()\\r\\n        polarity_matrix.reset_index(drop=True, inplace=True)\\r\\n\\r\\n        topic_matrix = topic_model.get_topic_table()\\r\\n        topic_matrix.reset_index(drop=True, inplace=True)\\r\\n        \\r\\n        self.final_data = pd.concat([self.df.dataset,polarity_matrix, topic_matrix], axis = 1)\\r\\n        self.final_data[\\'Date\\'] =  pd.to_datetime(self.final_data[\\'Date\\'])                \\r\\n\\r\\n        return self.final_data\\r\\n\\r\\n    def get_topic_polarity_plots(self,topic_num, topic_model, polarity_model):\\r\\n\\r\\n        if (topic_num < topic_model.get_num_topics() and topic_model.get_num_topics() > -1):\\r\\n\\r\\n            final_data = self.get_full_table(topic_model, polarity_model)\\r\\n            top_articles = [final_data.loc[(final_data[\\'Topic 1\\'] == topic_num)],final_data.loc[(final_data[\\'Topic 2\\'] == topic_num)],final_data.loc[(final_data[\\'Topic 3\\'] == topic_num)],final_data.loc[(final_data[\\'Topic 4\\'] == topic_num)],final_data.loc[(final_data[\\'Topic 5\\'] == topic_num)]]\\r\\n            articles_from_topic = pd.concat(top_articles, axis = 0)\\r\\n\\r\\n            plt.figure(figsize=(25,10))\\r\\n            plt.scatter(articles_from_topic[\\'Date\\'], articles_from_topic[\\'Polarity\\'])\\r\\n            plt.show()\\r\\n            plt.savefig(f\\'topic_{topic_num}_polarity_plot.png\\')\\r\\n            plt.clf()\\r\\n            plt.cla()\\r\\n            plt.close()\\r\\n\\r\\n\\r\\n        else: print(\\'invalid topic number\\')\\r\\n\\r\\n\\r\\n\\r\\n\\r\\n\\r\\n    \\r\\n\\r\\n\\r\\ndef lda_testing_script():\\r\\n\\r\\n    df = MyDataset(\\'Articles.csv\\')\\r\\n    lda_model = LDA_Topic_Model(df.preprocess_for_LDA())\\r\\n    lda_model.get_dominant_topics()\\r\\n    lda_model.get_topic_word_cloud(2)\\r\\n    lda_model.get_topic_word_dist(2)\\r\\n    lda_model.get_sentence_colors(2,4)\\r\\n    lda_model.get_sne_cluster()\\r\\n\\r\\ndef bert_testing_script():\\r\\n\\r\\n    df = MyDataset(\\'Articles.csv\\')\\r\\n    articles, dates = df.preprocess_for_bert()\\r\\n    bert_model = BERT_topic_Model(articles, dates)\\r\\n    bert_model.get_num_topics()\\r\\n    bert_model.get_topic_desc()\\r\\n    bert_model.show_topic_clusters()\\r\\n    bert_model.show_dynamic_topic_plots(10)\\r\\n\\r\\ndef vader_testing_script():\\r\\n\\r\\n    df = MyDataset(\\'Articles.csv\\')\\r\\n    vader_model = VADER_sentiment_analyzer(df.preprocess_for_bert())\\r\\n    vader_model.get_text_polarity()\\r\\n\\r\\ndef bert_s_testing_script():\\r\\n\\r\\n    df = MyDataset(\\'Articles.cvs\\')\\r\\n    articles, _ = df.preprocess_for_bert()\\r\\n    bert_s_model = BERT_Summarization_Model(articles)\\r\\n    bert_s_model.get_spec_text_sum()\\r\\n\\r\\ndef main():\\r\\n\\r\\n    # lda_testing_script()\\r\\n    # bert_testing_script()\\r\\n    # vader_testing_script()\\r\\n    # bert_s_testing_script()\\r\\n\\r\\n    # vader_model = NLP_Controller(\\'Articles.csv\\').sa_vader()\\r\\n    model = NLP_Controller(\\'Articles.csv\\').tm_bert()\\r\\n\\r\\n\\r\\nif __name__==\"__main__\":\\r\\n\\r\\n    main()'}"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 1
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Q4NsooKquauZ"
      },
      "source": [
        "## 2. Creating an NLP_Controller\n",
        "The first step to using this toolkit is to create a NLP_Controller object which you can use to deploy the various models included in it."
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "8ixKWB_BrAJd",
        "outputId": "e5a9fb93-be57-4824-dbeb-7736815470b6"
      },
      "source": [
        "from NLP4News import NLP_Controller\n",
        "\n",
        "con = NLP_Controller('Articles.csv')"
      ],
      "execution_count": 2,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/distributed/config.py:20: YAMLLoadWarning: calling yaml.load() without Loader=... is deprecated, as the default Loader is unsafe. Please read https://msg.pyyaml.org/load for full details.\n",
            "  defaults = yaml.load(f)\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "2MnTwdYSu4z_"
      },
      "source": [
        "## 3. Creating and Model and Accessing its Data\n",
        "Using the NLP_Controller object we can create a variety of models using our dataset whithout worrying about specific preprocessing tasks which are handeled by the controller for each model. "
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "4uZeaUHbkBbI"
      },
      "source": [
        "###3.1. Topic Modelling with BERT"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "JuL8tH8Hv3jW",
        "outputId": "5dd93a62-606d-4c68-8efe-fb3abca9dd4c"
      },
      "source": [
        "bert_topic_model = con.tm_bert()"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "/usr/local/lib/python3.7/dist-packages/numba/np/ufunc/parallel.py:363: NumbaWarning: The TBB threading layer requires TBB version 2019.5 or later i.e., TBB_INTERFACE_VERSION >= 11005. Found TBB_INTERFACE_VERSION = 9107. The TBB threading layer is disabled.\n",
            "  warnings.warn(problem)\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "qHMzM5UwPOx9",
        "outputId": "b0c4e293-5f7d-4fd6-f617-d2ceee8ad4bc"
      },
      "source": [
        "bert_topic_model.get_num_topics()"
      ],
      "execution_count": 16,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "64"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 16
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 422
        },
        "id": "eyHetD5_PTlh",
        "outputId": "0253d77f-06e2-4a5e-e56d-1b30d76888cb"
      },
      "source": [
        "bert_topic_model.get_topic_desc()"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
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              "\n",
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              "</style>\n",
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              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Topic</th>\n",
              "      <th>Count</th>\n",
              "      <th>Name</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>-1</td>\n",
              "      <td>793</td>\n",
              "      <td>-1_england_cricket_have_was</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>0</td>\n",
              "      <td>142</td>\n",
              "      <td>0_yen_tokyo_shares_markets</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>1</td>\n",
              "      <td>125</td>\n",
              "      <td>1_oil_crude_prices_barrel</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>2</td>\n",
              "      <td>87</td>\n",
              "      <td>2_china_chinese_beijing_investment</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>3</td>\n",
              "      <td>71</td>\n",
              "      <td>3_bangladesh_india_wickets_overs</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>59</th>\n",
              "      <td>58</td>\n",
              "      <td>11</td>\n",
              "      <td>58_sammy_indies_england_jordan</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>60</th>\n",
              "      <td>59</td>\n",
              "      <td>11</td>\n",
              "      <td>59_coup_turkey_turkish_tourism</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>61</th>\n",
              "      <td>60</td>\n",
              "      <td>10</td>\n",
              "      <td>60_bank_development_sector_financing</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>62</th>\n",
              "      <td>61</td>\n",
              "      <td>10</td>\n",
              "      <td>61_pso_kapco_debt_receivables</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>63</th>\n",
              "      <td>62</td>\n",
              "      <td>10</td>\n",
              "      <td>62_khan_fight_boxing_wbc</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>64 rows × 3 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "    Topic  Count                                  Name\n",
              "0      -1    793           -1_england_cricket_have_was\n",
              "1       0    142            0_yen_tokyo_shares_markets\n",
              "2       1    125             1_oil_crude_prices_barrel\n",
              "3       2     87    2_china_chinese_beijing_investment\n",
              "4       3     71      3_bangladesh_india_wickets_overs\n",
              "..    ...    ...                                   ...\n",
              "59     58     11        58_sammy_indies_england_jordan\n",
              "60     59     11        59_coup_turkey_turkish_tourism\n",
              "61     60     10  60_bank_development_sector_financing\n",
              "62     61     10         61_pso_kapco_debt_receivables\n",
              "63     62     10              62_khan_fight_boxing_wbc\n",
              "\n",
              "[64 rows x 3 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 17
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 667
        },
        "id": "EhDzF-7mSBGp",
        "outputId": "16f7cec8-821e-4cf3-be23-5ec4e5063529"
      },
      "source": [
        "bert_topic_model.model.visualize_topics()"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
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            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 487
        },
        "id": "kydXlB2bS3U4",
        "outputId": "d8c809d1-b161-4a71-952e-f825d711a3d3"
      },
      "source": [
        "topics_over_time = bert_topic_model.model.topics_over_time(bert_topic_model.articles, bert_topic_model.topics, bert_topic_model.dates, nr_bins=20)\n",
        "bert_topic_model.model.visualize_topics_over_time(topics_over_time, top_n_topics=bert_topic_model.get_num_topics())"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
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              "<html>\n",
              "<head><meta charset=\"utf-8\" /></head>\n",
              "<body>\n",
              "    <div>            <script src=\"https://cdnjs.cloudflare.com/ajax/libs/mathjax/2.7.5/MathJax.js?config=TeX-AMS-MML_SVG\"></script><script type=\"text/javascript\">if (window.MathJax) {MathJax.Hub.Config({SVG: {font: \"STIX-Web\"}});}</script>                <script type=\"text/javascript\">window.PlotlyConfig = {MathJaxConfig: 'local'};</script>\n",
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\"<b>Topic 10</b><br>Words: oil, crude, shale, production, barrel\", \"<b>Topic 10</b><br>Words: week, crude, oil, barrel, jobs\", \"<b>Topic 10</b><br>Words: crude, oil, barrels, barrel, russia\", \"<b>Topic 10</b><br>Words: crude, oil, cents, barrel, brent\", \"<b>Topic 10</b><br>Words: crude, oil, barrel, prices, barrels\", \"<b>Topic 10</b><br>Words: oil, prices, refined, barrel, crude\", \"<b>Topic 10</b><br>Words: crude, opec, eia, prices, barrels\", \"<b>Topic 10</b><br>Words: opec, oil, crude, prices, gulf\", \"<b>Topic 10</b><br>Words: crude, yields, investors, stocks, nasdaq\", \"<b>Topic 10</b><br>Words: oil, production, opec, cut, producers\"], \"marker\": {\"color\": \"#F0E442\"}, \"mode\": \"lines\", \"name\": \"10_oil_crude_prices_barrel\", \"type\": \"scatter\", \"x\": [\"2014-12-31T04:24:57.600000\", \"2015-02-10T19:12:00\", \"2015-03-23T14:24:00\", \"2015-05-03T09:36:00\", \"2015-06-13T04:48:00\", \"2015-07-24T00:00:00\", \"2015-09-02T19:12:00\", \"2015-10-13T14:24:00\", \"2015-11-23T09:36:00\", \"2016-01-03T04:48:00\", \"2016-02-13T00:00:00\", \"2016-03-24T19:12:00\", \"2016-05-04T14:24:00\", \"2016-07-25T04:48:00\", \"2016-09-04T00:00:00\", \"2016-10-14T19:12:00\", \"2016-11-24T14:24:00\", \"2017-01-04T09:36:00\"], \"y\": [2, 3, 2, 3, 3, 1, 2, 1, 1, 1, 2, 5, 6, 5, 1, 1, 1, 1]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 12</b><br>Words: petrol, litre, petroleum, diesel, kerosene\", \"<b>Topic 12</b><br>Words: litre, price, diesel, petroleum, petrol\", \"<b>Topic 12</b><br>Words: litre, ogra, price, petrol, diesel\", \"<b>Topic 12</b><br>Words: price, increase, litre, petroleum, petrol\", \"<b>Topic 12</b><br>Words: litre, price, per, diesel, petroleum\", \"<b>Topic 12</b><br>Words: lpg, price, petroleum, petrol, distributors\", \"<b>Topic 12</b><br>Words: litre, lpg, cylinder, petrol, diesel\", \"<b>Topic 12</b><br>Words: batteries, volta, litre, petrol, battery\", \"<b>Topic 12</b><br>Words: litre, diesel, petrol, petroleum, kerosene\", \"<b>Topic 12</b><br>Words: litre, diesel, petrol, petroleum, kerosene\", \"<b>Topic 12</b><br>Words: litre, rupees, petroleum, petrol, diesel\", \"<b>Topic 12</b><br>Words: litre, diesel, petrol, ogra, price\", \"<b>Topic 12</b><br>Words: litre, petroleum, diesel, ogra, petrol\", \"<b>Topic 12</b><br>Words: regulatory, petroleum, prices, increase, products\", \"<b>Topic 12</b><br>Words: petrol, diesel, prices, petroleum, price\", \"<b>Topic 12</b><br>Words: diesel, litre, petrol, petroleum, prices\", \"<b>Topic 12</b><br>Words: diesel, petrol, petroleum, kerosene, litre\"], \"marker\": {\"color\": \"#D55E00\"}, \"mode\": \"lines\", \"name\": \"12_litre_petrol_diesel_price\", \"type\": \"scatter\", \"x\": [\"2014-12-31T04:24:57.600000\", \"2015-02-10T19:12:00\", \"2015-03-23T14:24:00\", \"2015-05-03T09:36:00\", \"2015-07-24T00:00:00\", \"2015-09-02T19:12:00\", \"2015-10-13T14:24:00\", \"2015-11-23T09:36:00\", \"2016-01-03T04:48:00\", \"2016-03-24T19:12:00\", \"2016-05-04T14:24:00\", \"2016-06-14T09:36:00\", \"2016-07-25T04:48:00\", \"2016-09-04T00:00:00\", \"2016-11-24T14:24:00\", \"2017-01-04T09:36:00\", \"2017-02-14T04:48:00\"], \"y\": [4, 3, 5, 2, 2, 3, 3, 1, 2, 3, 1, 2, 2, 1, 1, 2, 2]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 14</b><br>Words: imf, franks, fund, pakistan, staff\", \"<b>Topic 14</b><br>Words: monetary, fund, pakistan, revenue, economy\", \"<b>Topic 14</b><br>Words: imf, eff, fund, extended, finance\", \"<b>Topic 14</b><br>Words: imf, growth, forecast, economies, economy\", \"<b>Topic 14</b><br>Words: financial, growth, imf, productivity, weakened\", \"<b>Topic 14</b><br>Words: imf, economic, economies, fund, monetary\", \"<b>Topic 14</b><br>Words: secp, integration, reforms, economy, finance\", \"<b>Topic 14</b><br>Words: imf, growth, forecast, economic, finance\", \"<b>Topic 14</b><br>Words: imf, monetary, japan, finance, fiscal\", \"<b>Topic 14</b><br>Words: imf, fiscal, fund, monetary, economic\", \"<b>Topic 14</b><br>Words: programme, imf, finance, net, sector\", \"<b>Topic 14</b><br>Words: bankruptcy, economies, restructuring, forecasts, liquidation\", \"<b>Topic 14</b><br>Words: reforms, economic, growth, finance, fund\"], \"marker\": {\"color\": \"#0072B2\"}, \"mode\": \"lines\", \"name\": \"14_growth_fund_finance_monetary\", \"type\": \"scatter\", \"x\": [\"2014-12-31T04:24:57.600000\", \"2015-02-10T19:12:00\", \"2015-05-03T09:36:00\", \"2015-06-13T04:48:00\", \"2015-11-23T09:36:00\", \"2016-01-03T04:48:00\", \"2016-02-13T00:00:00\", \"2016-03-24T19:12:00\", \"2016-05-04T14:24:00\", \"2016-06-14T09:36:00\", \"2016-07-25T04:48:00\", \"2016-09-04T00:00:00\", \"2016-10-14T19:12:00\"], \"y\": [1, 2, 2, 2, 1, 3, 1, 4, 7, 4, 5, 2, 2]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 17</b><br>Words: stock, investors, index, market, barrier\", \"<b>Topic 17</b><br>Words: index, kse, market, bearish, stock\", \"<b>Topic 17</b><br>Words: stock, market, karachi, stocks, investors\", \"<b>Topic 17</b><br>Words: kse, share, karachi, fertilizers, peg\", \"<b>Topic 17</b><br>Words: stock, trading, markets, market, index\", \"<b>Topic 17</b><br>Words: stock, markets, shanghai, trading, investors\", \"<b>Topic 17</b><br>Words: rupee, paisa, market, payments, closing\", \"<b>Topic 17</b><br>Words: filers, returns, payers, tax, filing\", \"<b>Topic 17</b><br>Words: banking, results, bank, ended, close\", \"<b>Topic 17</b><br>Words: stock, market, stocks, pakistan, closed\", \"<b>Topic 17</b><br>Words: stock, stocks, market, shares, securities\", \"<b>Topic 17</b><br>Words: cement, bank, close, rates, stock\", \"<b>Topic 17</b><br>Words: stock, investor, stake, shanghai, interest\", \"<b>Topic 17</b><br>Words: index, tensions, insaaf, pakistani, stock\", \"<b>Topic 17</b><br>Words: index, woolworths, ftse, stock, stocks\", \"<b>Topic 17</b><br>Words: trend, stock, business, index, uphill\"], \"marker\": {\"color\": \"#CC79A7\"}, \"mode\": \"lines\", \"name\": \"17_stock_stocks_karachi_close\", \"type\": \"scatter\", \"x\": [\"2014-12-31T04:24:57.600000\", \"2015-02-10T19:12:00\", \"2015-03-23T14:24:00\", \"2015-05-03T09:36:00\", \"2015-07-24T00:00:00\", \"2015-09-02T19:12:00\", \"2015-10-13T14:24:00\", \"2015-11-23T09:36:00\", \"2016-03-24T19:12:00\", \"2016-05-04T14:24:00\", \"2016-06-14T09:36:00\", \"2016-07-25T04:48:00\", \"2016-09-04T00:00:00\", \"2016-10-14T19:12:00\", \"2016-11-24T14:24:00\", \"2017-01-04T09:36:00\"], \"y\": [1, 1, 2, 1, 2, 1, 1, 1, 1, 3, 7, 8, 2, 1, 2, 1]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 19</b><br>Words: brunei, investment, venture, finance, financing\", \"<b>Topic 19</b><br>Words: rate, bank, interest, sbp, monetary\", \"<b>Topic 19</b><br>Words: bank, eurobonds, agriculture, economic, reserves\", \"<b>Topic 19</b><br>Words: moody, reforms, economic, upgraded, growth\", \"<b>Topic 19</b><br>Words: sbp, economy, depreciation, markets, economic\", \"<b>Topic 19</b><br>Words: cpi, bank, inflation, rate, decelerated\", \"<b>Topic 19</b><br>Words: fy, inflation, sbp, payments, rate\", \"<b>Topic 19</b><br>Words: economy, pml, government, pakistan, economic\", \"<b>Topic 19</b><br>Words: inflation, economic, government, pakistan, growth\", \"<b>Topic 19</b><br>Words: inflation, sbp, monetary, trends, growth\", \"<b>Topic 19</b><br>Words: inflation, growth, cut, pakistan, economic\", \"<b>Topic 19</b><br>Words: employment, corridor, economic, china, cpec\", \"<b>Topic 19</b><br>Words: coal, thar, rate, started, shaikh\", \"<b>Topic 19</b><br>Words: rate, fed, inflation, rates, sbp\", \"<b>Topic 19</b><br>Words: growth, macroeconomic, pakistan, reforms, inflation\", \"<b>Topic 19</b><br>Words: inflation, rates, october, rate, prices\", \"<b>Topic 19</b><br>Words: pakistan, bank, rate, economy, telecom\"], \"marker\": {\"color\": \"#E69F00\"}, \"mode\": \"lines\", \"name\": \"19_inflation_rate_growth_economic\", \"type\": \"scatter\", \"x\": [\"2014-12-31T04:24:57.600000\", \"2015-02-10T19:12:00\", \"2015-03-23T14:24:00\", \"2015-05-03T09:36:00\", \"2015-07-24T00:00:00\", \"2015-09-02T19:12:00\", \"2015-10-13T14:24:00\", \"2015-11-23T09:36:00\", \"2016-01-03T04:48:00\", \"2016-03-24T19:12:00\", \"2016-05-04T14:24:00\", \"2016-06-14T09:36:00\", \"2016-07-25T04:48:00\", \"2016-09-04T00:00:00\", \"2016-10-14T19:12:00\", \"2016-11-24T14:24:00\", \"2017-01-04T09:36:00\"], \"y\": [1, 2, 3, 3, 2, 1, 1, 1, 3, 1, 4, 1, 2, 3, 1, 2, 2]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 22</b><br>Words: oil, crude, prices, barrel, brent\", \"<b>Topic 22</b><br>Words: crude, oil, prices, barrel, brent\", \"<b>Topic 22</b><br>Words: yemen, oil, crude, prices, iran\", \"<b>Topic 22</b><br>Words: crude, oil, yemen, prices, barrel\", \"<b>Topic 22</b><br>Words: oil, crude, barrels, prices, barrel\", \"<b>Topic 22</b><br>Words: oil, crude, prices, barrel, shale\", \"<b>Topic 22</b><br>Words: delivery, crude, demand, inventories, barrel\", \"<b>Topic 22</b><br>Words: oil, prices, crude, dow, dupont\", \"<b>Topic 22</b><br>Words: oil, prices, crude, barrel, iranian\", \"<b>Topic 22</b><br>Words: gasoil, diesel, bpd, forecast, oil\", \"<b>Topic 22</b><br>Words: sales, gm, automaker, automotive, incentives\", \"<b>Topic 22</b><br>Words: food, cereals, prices, dairy, oils\", \"<b>Topic 22</b><br>Words: crude, oil, barrel, drillers, rigs\"], \"marker\": {\"color\": \"#56B4E9\"}, \"mode\": \"lines\", \"name\": \"22_oil_crude_prices_barrel\", \"type\": \"scatter\", \"x\": [\"2014-12-31T04:24:57.600000\", \"2015-02-10T19:12:00\", \"2015-03-23T14:24:00\", \"2015-05-03T09:36:00\", \"2015-06-13T04:48:00\", \"2015-09-02T19:12:00\", \"2015-10-13T14:24:00\", \"2015-11-23T09:36:00\", \"2016-01-03T04:48:00\", \"2016-03-24T19:12:00\", \"2016-10-14T19:12:00\", \"2017-01-04T09:36:00\", \"2017-02-14T04:48:00\"], \"y\": [6, 7, 4, 1, 3, 1, 1, 1, 1, 1, 1, 2, 2]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 37</b><br>Words: hsbc, swiss, fifa, private, accounts\", \"<b>Topic 37</b><br>Words: pilots, fifa, france, staff, euros\", \"<b>Topic 37</b><br>Words: fifa, ethics, valcke, corruption, zurich\", \"<b>Topic 37</b><br>Words: fifa, swiss, ethics, zurich, michel\", \"<b>Topic 37</b><br>Words: fifa, interference, soccer, ethics, committee\", \"<b>Topic 37</b><br>Words: fifa, platini, innocence, ban, swiss\"], \"marker\": {\"color\": \"#009E73\"}, \"mode\": \"lines\", \"name\": \"37_fifa_swiss_soccer_banned\", \"type\": \"scatter\", \"x\": [\"2014-12-31T04:24:57.600000\", \"2015-09-02T19:12:00\", \"2016-01-03T04:48:00\", \"2016-02-13T00:00:00\", \"2016-05-04T14:24:00\", \"2016-07-25T04:48:00\"], \"y\": [1, 1, 5, 7, 5, 1]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 42</b><br>Words: saudi, oil, abdullah, arabia, change\", \"<b>Topic 42</b><br>Words: subsidies, saudi, gulf, spending, breakeven\", \"<b>Topic 42</b><br>Words: saudi, arabia, opec, iran, cleric\", \"<b>Topic 42</b><br>Words: saudi, arab, crude, prices, arabia\", \"<b>Topic 42</b><br>Words: tariffs, saudi, electricity, riyadh, arabia\", \"<b>Topic 42</b><br>Words: saudi, arabia, deficit, mohammed, riyadh\", \"<b>Topic 42</b><br>Words: saudi, riyals, visa, fees, visas\", \"<b>Topic 42</b><br>Words: saudi, astana, visa, kazakhstan, uzbekistan\", \"<b>Topic 42</b><br>Words: saudi, saudis, arabia, workers, oil\"], \"marker\": {\"color\": \"#F0E442\"}, \"mode\": \"lines\", \"name\": \"42_saudi_arabia_oil_dhabi\", \"type\": \"scatter\", \"x\": [\"2014-12-31T04:24:57.600000\", \"2015-05-03T09:36:00\", \"2016-01-03T04:48:00\", \"2016-02-13T00:00:00\", \"2016-03-24T19:12:00\", \"2016-05-04T14:24:00\", \"2016-10-14T19:12:00\", \"2016-11-24T14:24:00\", \"2017-02-14T04:48:00\"], \"y\": [1, 1, 1, 2, 1, 5, 1, 2, 4]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 48</b><br>Words: electric, power, notification, tariff, fuel\", \"<b>Topic 48</b><br>Words: electric, regulatory, power, adjustment, reduction\", \"<b>Topic 48</b><br>Words: decrease, power, electric, purchasing, electricity\", \"<b>Topic 48</b><br>Words: electric, tariff, power, relief, decrease\", \"<b>Topic 48</b><br>Words: nepra, tariff, electric, adjustment, regulatory\", \"<b>Topic 48</b><br>Words: tariff, electricity, khushab, electric, solar\", \"<b>Topic 48</b><br>Words: nepra, electric, tariff, approved, adjustment\", \"<b>Topic 48</b><br>Words: tariff, nepra, electric, adjustment, reduction\", \"<b>Topic 48</b><br>Words: electric, nepra, fuel, power, unit\", \"<b>Topic 48</b><br>Words: tariff, reduction, electric, cppa, adjustment\", \"<b>Topic 48</b><br>Words: power, tariff, nepra, electric, regulatory\"], \"marker\": {\"color\": \"#D55E00\"}, \"mode\": \"lines\", \"name\": \"48_nepra_tariff_electric_adjustment\", \"type\": \"scatter\", \"x\": [\"2014-12-31T04:24:57.600000\", \"2015-02-10T19:12:00\", \"2015-03-23T14:24:00\", \"2015-05-03T09:36:00\", \"2015-06-13T04:48:00\", \"2015-09-02T19:12:00\", \"2015-10-13T14:24:00\", \"2015-11-23T09:36:00\", \"2016-01-03T04:48:00\", \"2016-02-13T00:00:00\", \"2016-10-14T19:12:00\"], \"y\": [2, 1, 1, 2, 2, 1, 1, 3, 1, 2, 1]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 51</b><br>Words: load, shedding, power, mw, electric\", \"<b>Topic 51</b><br>Words: power, electricity, mw, grid, loadshedding\", \"<b>Topic 51</b><br>Words: power, projects, megawatts, mw, electricity\", \"<b>Topic 51</b><br>Words: ramazan, load, shedding, power, supply\", \"<b>Topic 51</b><br>Words: projects, ambassador, sector, energy, country\", \"<b>Topic 51</b><br>Words: power, projects, coal, mw, electricity\", \"<b>Topic 51</b><br>Words: power, projects, electricity, mw, grid\", \"<b>Topic 51</b><br>Words: duration, power, loadshedding, megawatts, electricity\", \"<b>Topic 51</b><br>Words: paec, power, grid, unit, electricity\"], \"marker\": {\"color\": \"#0072B2\"}, \"mode\": \"lines\", \"name\": \"51_power_mw_projects_electricity\", \"type\": \"scatter\", \"x\": [\"2014-12-31T04:24:57.600000\", \"2015-02-10T19:12:00\", \"2015-03-23T14:24:00\", \"2015-05-03T09:36:00\", \"2015-06-13T04:48:00\", \"2015-09-02T19:12:00\", \"2016-02-13T00:00:00\", \"2016-05-04T14:24:00\", \"2016-10-14T19:12:00\"], \"y\": [2, 1, 2, 1, 1, 3, 2, 1, 1]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 54</b><br>Words: petrol, price, gas, consumers, rs\", \"<b>Topic 54</b><br>Words: cng, stations, ssgc, closure, sindh\", \"<b>Topic 54</b><br>Words: cng, stations, reopen, gas, sngpl\", \"<b>Topic 54</b><br>Words: cng, closure, reopen, gas, stations\", \"<b>Topic 54</b><br>Words: gas, closed, supply, ssgc, sindh\", \"<b>Topic 54</b><br>Words: cng, gas, price, compressed, pumping\", \"<b>Topic 54</b><br>Words: cng, gas, inspection, authority, associations\", \"<b>Topic 54</b><br>Words: cng, owners, litre, stations, prices\"], \"marker\": {\"color\": \"#CC79A7\"}, \"mode\": \"lines\", \"name\": \"54_cng_gas_owners_reopen\", \"type\": \"scatter\", \"x\": [\"2014-12-31T04:24:57.600000\", \"2015-02-10T19:12:00\", \"2015-05-03T09:36:00\", \"2015-06-13T04:48:00\", \"2015-07-24T00:00:00\", \"2016-02-13T00:00:00\", \"2016-07-25T04:48:00\", \"2016-11-24T14:24:00\"], \"y\": [1, 1, 1, 1, 2, 1, 5, 1]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 13</b><br>Words: richest, billion, founder, apple, microsoft\", \"<b>Topic 13</b><br>Words: digital, microsoft, media, news, apple\", \"<b>Topic 13</b><br>Words: vw, lawsuits, carmaker, german, emissions\", \"<b>Topic 13</b><br>Words: tribune, volkswagen, supervisory, vw, company\", \"<b>Topic 13</b><br>Words: apple, inc, volkswagen, fund, money\", \"<b>Topic 13</b><br>Words: vda, registrations, car, forbes, koch\", \"<b>Topic 13</b><br>Words: huffington, huffpost, venture, founder, owns\", \"<b>Topic 13</b><br>Words: digital, advertising, print, revenues, revenue\", \"<b>Topic 13</b><br>Words: softbank, trump, investment, inc, invest\", \"<b>Topic 13</b><br>Words: trump, inc, uber, autonomous, companies\", \"<b>Topic 13</b><br>Words: uber, vehicle, driving, vehicles, accident\"], \"marker\": {\"color\": \"#E69F00\"}, \"mode\": \"lines\", \"name\": \"13_apple_company_uber_volkswagen\", \"type\": \"scatter\", \"x\": [\"2015-02-10T19:12:00\", \"2015-07-24T00:00:00\", \"2016-02-13T00:00:00\", \"2016-03-24T19:12:00\", \"2016-05-04T14:24:00\", \"2016-06-14T09:36:00\", \"2016-07-25T04:48:00\", \"2016-10-14T19:12:00\", \"2016-11-24T14:24:00\", \"2017-01-04T09:36:00\", \"2017-02-14T04:48:00\"], \"y\": [2, 3, 2, 5, 5, 3, 4, 1, 1, 5, 5]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 23</b><br>Words: hotels, dollars, bookings, australia, cup\", \"<b>Topic 23</b><br>Words: waca, perth, smith, test, australia\", \"<b>Topic 23</b><br>Words: adelaide, cricket, australia, players, ball\", \"<b>Topic 23</b><br>Words: adelaide, cricket, australia, play, zealand\", \"<b>Topic 23</b><br>Words: india, cricket, zealand, odi, adelaide\", \"<b>Topic 23</b><br>Words: cricket, test, floodlights, lights, fixture\"], \"marker\": {\"color\": \"#56B4E9\"}, \"mode\": \"lines\", \"name\": \"23_cricket_australia_adelaide_zealand\", \"type\": \"scatter\", \"x\": [\"2015-02-10T19:12:00\", \"2016-01-03T04:48:00\", \"2016-03-24T19:12:00\", \"2016-05-04T14:24:00\", \"2016-06-14T09:36:00\", \"2016-07-25T04:48:00\"], \"y\": [1, 2, 8, 12, 6, 1]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 33</b><br>Words: euro, dollar, europe, fed, bond\", \"<b>Topic 33</b><br>Words: greece, euro, fed, reserve, yen\", \"<b>Topic 33</b><br>Words: dollar, euro, dax, paris, frankfurt\", \"<b>Topic 33</b><br>Words: euro, fed, ecb, rate, reserve\", \"<b>Topic 33</b><br>Words: belgian, brussels, stocks, fell, european\", \"<b>Topic 33</b><br>Words: europe, eu, european, fell, british\", \"<b>Topic 33</b><br>Words: vecchio, dollar, consumers, consumer, euro\", \"<b>Topic 33</b><br>Words: clinton, percent, polls, markets, presidential\", \"<b>Topic 33</b><br>Words: dollar, franc, percent, yen, euro\", \"<b>Topic 33</b><br>Words: pound, dollar, peers, gains, investors\"], \"marker\": {\"color\": \"#009E73\"}, \"mode\": \"lines\", \"name\": \"33_clinton_trump_dollar_euro\", \"type\": \"scatter\", \"x\": [\"2015-02-10T19:12:00\", \"2015-06-13T04:48:00\", \"2015-10-13T14:24:00\", \"2015-11-23T09:36:00\", \"2016-02-13T00:00:00\", \"2016-06-14T09:36:00\", \"2016-07-25T04:48:00\", \"2016-10-14T19:12:00\", \"2016-11-24T14:24:00\", \"2017-01-04T09:36:00\"], \"y\": [1, 3, 2, 2, 1, 2, 2, 7, 1, 1]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 36</b><br>Words: lng, coal, khaqan, liquefied, geo\", \"<b>Topic 36</b><br>Words: gas, ssgcl, fsru, lng, ipps\", \"<b>Topic 36</b><br>Words: lng, liquefied, gas, doha, pipeline\", \"<b>Topic 36</b><br>Words: prebble, announced, cater, signed, parties\", \"<b>Topic 36</b><br>Words: qatar, lng, abbasi, agreements, import\", \"<b>Topic 36</b><br>Words: lng, qatar, import, mmcf, liquefied\", \"<b>Topic 36</b><br>Words: iran, baglay, port, afghanistan, connectivity\", \"<b>Topic 36</b><br>Words: qatar, tower, doha, designed, mohammed\", \"<b>Topic 36</b><br>Words: rosneft, putin, russian, russia, aramco\", \"<b>Topic 36</b><br>Words: consultations, regional, russia, exchanged, connectivity\", \"<b>Topic 36</b><br>Words: psx, treaty, deal, signed, exchanges\", \"<b>Topic 36</b><br>Words: fund, rkiye, russian, moscow, erdogan\"], \"marker\": {\"color\": \"#F0E442\"}, \"mode\": \"lines\", \"name\": \"36_lng_rosneft_qatar_russian\", \"type\": \"scatter\", \"x\": [\"2015-02-10T19:12:00\", \"2015-03-23T14:24:00\", \"2015-10-13T14:24:00\", \"2015-11-23T09:36:00\", \"2016-01-03T04:48:00\", \"2016-02-13T00:00:00\", \"2016-05-04T14:24:00\", \"2016-06-14T09:36:00\", \"2016-10-14T19:12:00\", \"2016-11-24T14:24:00\", \"2017-01-04T09:36:00\", \"2017-02-14T04:48:00\"], \"y\": [2, 1, 2, 1, 2, 1, 1, 1, 2, 1, 4, 2]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 49</b><br>Words: tax, fbr, taxpayers, revenue, income\", \"<b>Topic 49</b><br>Words: tax, fbr, income, filing, revenue\", \"<b>Topic 49</b><br>Words: billion, collection, fbr, revenue, tax\", \"<b>Topic 49</b><br>Words: fbr, tax, revenue, scheme, compliance\", \"<b>Topic 49</b><br>Words: fbr, tax, swiss, division, authorities\", \"<b>Topic 49</b><br>Words: fbr, tax, filing, taxpayers, returns\", \"<b>Topic 49</b><br>Words: fbr, tax, finance, stakeholders, revenue\", \"<b>Topic 49</b><br>Words: valuation, fbr, tax, revenue, cities\"], \"marker\": {\"color\": \"#D55E00\"}, \"mode\": \"lines\", \"name\": \"49_fbr_tax_revenue_vehicles\", \"type\": \"scatter\", \"x\": [\"2015-02-10T19:12:00\", \"2015-07-24T00:00:00\", \"2015-09-02T19:12:00\", \"2016-02-13T00:00:00\", \"2016-03-24T19:12:00\", \"2016-05-04T14:24:00\", \"2016-06-14T09:36:00\", \"2016-07-25T04:48:00\"], \"y\": [1, 4, 1, 2, 1, 1, 1, 5]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 52</b><br>Words: sim, nokia, mobile, phone, digital\", \"<b>Topic 52</b><br>Words: mobile, phones, manufacture, phone, manufacturing\", \"<b>Topic 52</b><br>Words: broadband, mobile, service, ngms, qos\", \"<b>Topic 52</b><br>Words: futuretech, iphone, stores, offers, advance\", \"<b>Topic 52</b><br>Words: mobile, smartphones, telecom, smartphone, imports\", \"<b>Topic 52</b><br>Words: mobile, million, phone, telecom, imports\", \"<b>Topic 52</b><br>Words: mobile, smartphones, sms, phone, phones\", \"<b>Topic 52</b><br>Words: mobile, phone, telecom, smartphones, customers\", \"<b>Topic 52</b><br>Words: jio, mobile, phone, telecom, ambani\", \"<b>Topic 52</b><br>Words: mobile, telecom, broadband, gst, internet\"], \"marker\": {\"color\": \"#0072B2\"}, \"mode\": \"lines\", \"name\": \"52_mobile_phone_telecom_broadband\", \"type\": \"scatter\", \"x\": [\"2015-02-10T19:12:00\", \"2015-03-23T14:24:00\", \"2015-06-13T04:48:00\", \"2015-10-13T14:24:00\", \"2016-02-13T00:00:00\", \"2016-03-24T19:12:00\", \"2016-05-04T14:24:00\", \"2016-06-14T09:36:00\", \"2016-07-25T04:48:00\", \"2016-10-14T19:12:00\"], \"y\": [1, 1, 1, 1, 1, 1, 2, 3, 2, 1]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 40</b><br>Words: budget, billion, tax, fiscal, sector\", \"<b>Topic 40</b><br>Words: budget, allocated, rupees, allocation, projects\", \"<b>Topic 40</b><br>Words: projects, division, homeless, rehabilitation, roads\", \"<b>Topic 40</b><br>Words: stipend, beneficiaries, bisp, per, payable\", \"<b>Topic 40</b><br>Words: rupees, billion, budget, fiscal, tax\", \"<b>Topic 40</b><br>Words: rupees, budget, billion, fiscal, prime\", \"<b>Topic 40</b><br>Words: earning, passport, billion, fee, passports\", \"<b>Topic 40</b><br>Words: tax, parliamentarians, directories, publishing, approved\"], \"marker\": {\"color\": \"#CC79A7\"}, \"mode\": \"lines\", \"name\": \"40_rupees_budget_billion_tax\", \"type\": \"scatter\", \"x\": [\"2015-05-03T09:36:00\", \"2015-06-13T04:48:00\", \"2015-10-13T14:24:00\", \"2016-01-03T04:48:00\", \"2016-02-13T00:00:00\", \"2016-05-04T14:24:00\", \"2016-07-25T04:48:00\", \"2016-09-04T00:00:00\"], \"y\": [7, 3, 1, 1, 1, 4, 1, 1]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 41</b><br>Words: kasb, bank, moratorium, depositors, stakeholders\", \"<b>Topic 41</b><br>Words: transaction, accounts, waived, deducted, deduction\", \"<b>Topic 41</b><br>Words: banks, bank, transaction, institutions, corporation\", \"<b>Topic 41</b><br>Words: sbp, funding, bank, terrorism, accounts\", \"<b>Topic 41</b><br>Words: banknote, banknotes, demonetized, tender, notification\", \"<b>Topic 41</b><br>Words: banknotes, banknote, sbp, waived, bank\", \"<b>Topic 41</b><br>Words: banknotes, banknote, denominations, issuance, tender\", \"<b>Topic 41</b><br>Words: waived, loans, borrowers, coin, nbp\", \"<b>Topic 41</b><br>Words: bank, notes, waived, loans, borrowers\", \"<b>Topic 41</b><br>Words: notes, atm, bank, withdrew, sbi\"], \"marker\": {\"color\": \"#E69F00\"}, \"mode\": \"lines\", \"name\": \"41_waived_loans_borrowers_bank\", \"type\": \"scatter\", \"x\": [\"2015-05-03T09:36:00\", \"2015-06-13T04:48:00\", \"2015-11-23T09:36:00\", \"2016-01-03T04:48:00\", \"2016-05-04T14:24:00\", \"2016-06-14T09:36:00\", \"2016-07-25T04:48:00\", \"2016-10-14T19:12:00\", \"2016-11-24T14:24:00\", \"2017-02-14T04:48:00\"], \"y\": [1, 2, 1, 1, 1, 2, 1, 5, 3, 1]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 47</b><br>Words: arctic, alaska, oil, drilling, fossil\", \"<b>Topic 47</b><br>Words: opec, output, oil, saudi, cartel\", \"<b>Topic 47</b><br>Words: opec, bpd, oil, demand, production\", \"<b>Topic 47</b><br>Words: opec, iran, oil, sanctions, saudi\", \"<b>Topic 47</b><br>Words: opec, saudi, iran, oil, arabia\", \"<b>Topic 47</b><br>Words: opec, bpd, saudi, oil, iran\", \"<b>Topic 47</b><br>Words: opec, iran, output, oil, quotas\", \"<b>Topic 47</b><br>Words: opec, bpd, saudi, oil, production\", \"<b>Topic 47</b><br>Words: bpd, opec, production, oil, saudi\"], \"marker\": {\"color\": \"#56B4E9\"}, \"mode\": \"lines\", \"name\": \"47_opec_bpd_oil_saudi\", \"type\": \"scatter\", \"x\": [\"2015-05-03T09:36:00\", \"2015-11-23T09:36:00\", \"2016-01-03T04:48:00\", \"2016-02-13T00:00:00\", \"2016-05-04T14:24:00\", \"2016-09-04T00:00:00\", \"2016-10-14T19:12:00\", \"2016-11-24T14:24:00\", \"2017-01-04T09:36:00\"], \"y\": [1, 1, 1, 1, 2, 2, 1, 5, 3]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 60</b><br>Words: funds, megawatt, megawatts, power, electricity\", \"<b>Topic 60</b><br>Words: barrage, rehabilitation, barrages, irrigation, sbip\", \"<b>Topic 60</b><br>Words: motorway, installments, kilometer, duration, islamabad\", \"<b>Topic 60</b><br>Words: sector, assistance, package, reforms, development\", \"<b>Topic 60</b><br>Words: ramzan, package, ecc, providing, secretariat\", \"<b>Topic 60</b><br>Words: sector, enterprises, financing, development, bank\", \"<b>Topic 60</b><br>Words: bank, financing, africa, countries, nations\"], \"marker\": {\"color\": \"#009E73\"}, \"mode\": \"lines\", \"name\": \"60_bank_development_sector_financing\", \"type\": \"scatter\", \"x\": [\"2015-05-03T09:36:00\", \"2015-06-13T04:48:00\", \"2015-10-13T14:24:00\", \"2016-03-24T19:12:00\", \"2016-05-04T14:24:00\", \"2016-06-14T09:36:00\", \"2017-02-14T04:48:00\"], \"y\": [1, 1, 1, 2, 1, 2, 2]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 16</b><br>Words: gold, ounce, price, lowest, dollar\", \"<b>Topic 16</b><br>Words: gold, ounce, palladium, platinum, dollar\", \"<b>Topic 16</b><br>Words: gold, ounce, dollar, hikes, rates\", \"<b>Topic 16</b><br>Words: gold, ounce, metal, spot, dollar\", \"<b>Topic 16</b><br>Words: gold, ounce, bullion, dollar, spot\", \"<b>Topic 16</b><br>Words: gold, dollar, ounce, metal, fed\", \"<b>Topic 16</b><br>Words: gold, ounce, dollar, metal, rates\", \"<b>Topic 16</b><br>Words: silver, rate, gmt, rates, safe\", \"<b>Topic 16</b><br>Words: ounce, yellen, rates, fed, dollar\", \"<b>Topic 16</b><br>Words: gold, ounce, dollar, percent, hike\", \"<b>Topic 16</b><br>Words: mint, gold, liberty, coins, coin\"], \"marker\": {\"color\": \"#F0E442\"}, \"mode\": \"lines\", \"name\": \"16_gold_ounce_dollar_metal\", \"type\": \"scatter\", \"x\": [\"2015-06-13T04:48:00\", \"2015-07-24T00:00:00\", \"2015-11-23T09:36:00\", \"2016-01-03T04:48:00\", \"2016-02-13T00:00:00\", \"2016-03-24T19:12:00\", \"2016-05-04T14:24:00\", \"2016-06-14T09:36:00\", \"2016-07-25T04:48:00\", \"2016-10-14T19:12:00\", \"2017-01-04T09:36:00\"], \"y\": [2, 1, 2, 6, 5, 4, 8, 3, 1, 2, 1]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 43</b><br>Words: safety, airline, fares, aviation, unsafe\", \"<b>Topic 43</b><br>Words: airport, embarkation, passengers, aviation, pia\", \"<b>Topic 43</b><br>Words: discount, pia, offer, airline, passengers\", \"<b>Topic 43</b><br>Words: pia, protest, ishaq, airlines, government\", \"<b>Topic 43</b><br>Words: pia, airlines, passengers, fares, airline\", \"<b>Topic 43</b><br>Words: pia, airline, service, operational, airlines\", \"<b>Topic 43</b><br>Words: cigarette, rules, tobacco, reducing, aircraft\", \"<b>Topic 43</b><br>Words: pia, aircraft, airlines, plane, boeing\", \"<b>Topic 43</b><br>Words: pia, aircraft, london, flights, passengers\", \"<b>Topic 43</b><br>Words: aircraft, grooming, airlines, airline, lease\"], \"marker\": {\"color\": \"#D55E00\"}, \"mode\": \"lines\", \"name\": \"43_aircraft_airlines_airline_passengers\", \"type\": \"scatter\", \"x\": [\"2015-06-13T04:48:00\", \"2015-07-24T00:00:00\", \"2015-09-02T19:12:00\", \"2015-11-23T09:36:00\", \"2016-01-03T04:48:00\", \"2016-02-13T00:00:00\", \"2016-03-24T19:12:00\", \"2016-07-25T04:48:00\", \"2016-09-04T00:00:00\", \"2016-10-14T19:12:00\"], \"y\": [3, 1, 1, 1, 3, 2, 1, 2, 1, 3]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 18</b><br>Words: onions, export, exports, containers, exporter\", \"<b>Topic 18</b><br>Words: rice, farmers, groundwater, crop, seedlings\", \"<b>Topic 18</b><br>Words: seeds, harvest, flowers, crop, sunflower\", \"<b>Topic 18</b><br>Words: exports, poultry, soybean, cotton, rice\", \"<b>Topic 18</b><br>Words: cotton, exports, export, fruit, farmers\", \"<b>Topic 18</b><br>Words: exports, cotton, million, jewellary, year\", \"<b>Topic 18</b><br>Words: cotton, exports, million, india, trade\", \"<b>Topic 18</b><br>Words: imports, cotton, exports, palm, million\", \"<b>Topic 18</b><br>Words: exports, fish, million, country, mandarins\"], \"marker\": {\"color\": \"#0072B2\"}, \"mode\": \"lines\", \"name\": \"18_exports_cotton_million_imports\", \"type\": \"scatter\", \"x\": [\"2015-07-24T00:00:00\", \"2015-09-02T19:12:00\", \"2016-03-24T19:12:00\", \"2016-05-04T14:24:00\", \"2016-06-14T09:36:00\", \"2016-07-25T04:48:00\", \"2016-09-04T00:00:00\", \"2016-10-14T19:12:00\", \"2016-11-24T14:24:00\"], \"y\": [1, 1, 1, 7, 6, 11, 2, 3, 2]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 44</b><br>Words: volkswagen, car, cars, vehicles, honda\", \"<b>Topic 44</b><br>Words: apparel, car, manufacturing, manufacturers, employment\", \"<b>Topic 44</b><br>Words: units, production, pakistan, growth, market\", \"<b>Topic 44</b><br>Words: manufacturing, textile, bmi, agribusiness, energy\", \"<b>Topic 44</b><br>Words: business, regulations, economies, ff, improved\", \"<b>Topic 44</b><br>Words: kia, cars, drivers, vehicles, manufacturing\", \"<b>Topic 44</b><br>Words: investment, ceo, growth, gdp, business\", \"<b>Topic 44</b><br>Words: bulgurlu, appliances, refrigerators, forecast, turkey\"], \"marker\": {\"color\": \"#CC79A7\"}, \"mode\": \"lines\", \"name\": \"44_manufacturing_textile_growth_business\", \"type\": \"scatter\", \"x\": [\"2015-07-24T00:00:00\", \"2016-05-04T14:24:00\", \"2016-06-14T09:36:00\", \"2016-07-25T04:48:00\", \"2016-10-14T19:12:00\", \"2016-11-24T14:24:00\", \"2017-01-04T09:36:00\", \"2017-02-14T04:48:00\"], \"y\": [1, 3, 3, 5, 1, 2, 1, 2]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 15</b><br>Words: sons, undertaking, hurled, litigation, dar\", \"<b>Topic 15</b><br>Words: india, cricket, himachal, pradesh, dharamsala\", \"<b>Topic 15</b><br>Words: cricket, pakistan, sri, india, lankan\", \"<b>Topic 15</b><br>Words: security, cricket, commandos, rashid, certificate\", \"<b>Topic 15</b><br>Words: cricket, india, lions, asiatic, permission\", \"<b>Topic 15</b><br>Words: dcns, submarines, security, leak, defence\"], \"marker\": {\"color\": \"#E69F00\"}, \"mode\": \"lines\", \"name\": \"15_india_cricket_himachal_indian\", \"type\": \"scatter\", \"x\": [\"2015-09-02T19:12:00\", \"2016-02-13T00:00:00\", \"2016-03-24T19:12:00\", \"2016-05-04T14:24:00\", \"2016-06-14T09:36:00\", \"2016-07-25T04:48:00\"], \"y\": [1, 25, 3, 2, 4, 1]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 61</b><br>Words: sacrificial, animals, cattle, camels, cows\", \"<b>Topic 61</b><br>Words: billion, recoveries, power, benefit, succeeded\", \"<b>Topic 61</b><br>Words: billion, debt, obligations, kapco, government\", \"<b>Topic 61</b><br>Words: pso, kapco, wapda, receivables, power\", \"<b>Topic 61</b><br>Words: sbp, annum, market, money, return\"], \"marker\": {\"color\": \"#56B4E9\"}, \"mode\": \"lines\", \"name\": \"61_pso_kapco_debt_receivables\", \"type\": \"scatter\", \"x\": [\"2015-09-02T19:12:00\", \"2016-01-03T04:48:00\", \"2016-06-14T09:36:00\", \"2016-07-25T04:48:00\", \"2016-09-04T00:00:00\"], \"y\": [1, 1, 1, 6, 1]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 59</b><br>Words: turkey, turkish, nato, coup, cancelled\", \"<b>Topic 59</b><br>Words: istanbul, turkish, evacuated, bomber, governor\", \"<b>Topic 59</b><br>Words: coup, turkish, erdogan, istanbul, recep\", \"<b>Topic 59</b><br>Words: coup, turkey, tourism, lira, cancelled\", \"<b>Topic 59</b><br>Words: turkey, tourism, visitor, turkish, istanbul\", \"<b>Topic 59</b><br>Words: hotel, turkey, embassy, loan, buildings\", \"<b>Topic 59</b><br>Words: fund, wealth, turkish, turkey, assets\"], \"marker\": {\"color\": \"#009E73\"}, \"mode\": \"lines\", \"name\": \"59_coup_turkey_turkish_tourism\", \"type\": \"scatter\", \"x\": [\"2015-10-13T14:24:00\", \"2016-02-13T00:00:00\", \"2016-06-14T09:36:00\", \"2016-07-25T04:48:00\", \"2016-09-04T00:00:00\", \"2016-10-14T19:12:00\", \"2017-01-04T09:36:00\"], \"y\": [1, 1, 1, 5, 1, 1, 1]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 3</b><br>Words: awards, iris, achievement, agencies, standards\", \"<b>Topic 3</b><br>Words: runs, bangladesh, overs, wickets, india\", \"<b>Topic 3</b><br>Words: bangladesh, india, wickets, overs, balls\", \"<b>Topic 3</b><br>Words: runs, bangladesh, india, wickets, zealand\", \"<b>Topic 3</b><br>Words: ke, award, won, pakistan, occupational\", \"<b>Topic 3</b><br>Words: kicks, records, bangladesh, record, martial\", \"<b>Topic 3</b><br>Words: asia, awards, creativity, ceo, pakistan\"], \"marker\": {\"color\": \"#F0E442\"}, \"mode\": \"lines\", \"name\": \"3_bangladesh_india_wickets_overs\", \"type\": \"scatter\", \"x\": [\"2015-11-23T09:36:00\", \"2016-01-03T04:48:00\", \"2016-02-13T00:00:00\", \"2016-03-24T19:12:00\", \"2016-05-04T14:24:00\", \"2016-06-14T09:36:00\", \"2016-11-24T14:24:00\"], \"y\": [1, 15, 40, 10, 2, 2, 1]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 9</b><br>Words: stokes, bairstow, runs, england, balls\", \"<b>Topic 9</b><br>Words: england, bairstow, wicket, innings, stokes\", \"<b>Topic 9</b><br>Words: guys, england, south, walked, abbott\", \"<b>Topic 9</b><br>Words: bairstow, england, hales, lanka, cook\", \"<b>Topic 9</b><br>Words: england, lanka, hales, bairstow, cook\", \"<b>Topic 9</b><br>Words: innings, cook, hales, out, off\", \"<b>Topic 9</b><br>Words: foodpanda, restaurants, discounts, food, kitchens\"], \"marker\": {\"color\": \"#D55E00\"}, \"mode\": \"lines\", \"name\": \"9_england_bairstow_hales_cook\", \"type\": \"scatter\", \"x\": [\"2015-11-23T09:36:00\", \"2016-01-03T04:48:00\", \"2016-02-13T00:00:00\", \"2016-05-04T14:24:00\", \"2016-06-14T09:36:00\", \"2016-07-25T04:48:00\", \"2016-11-24T14:24:00\"], \"y\": [2, 7, 1, 14, 13, 3, 1]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 11</b><br>Words: amir, mohammad, visa, cricket, bowler\", \"<b>Topic 11</b><br>Words: amir, cricket, pakistan, mohammad, mcl\", \"<b>Topic 11</b><br>Words: crowe, cricket, fixing, video, flanagan\", \"<b>Topic 11</b><br>Words: amir, he, comeback, cricket, moeen\", \"<b>Topic 11</b><br>Words: amir, visa, england, fixing, mohammad\", \"<b>Topic 11</b><br>Words: amir, cricket, mohammad, pakistan, bowler\", \"<b>Topic 11</b><br>Words: airports, dubai, flights, emirates, airport\"], \"marker\": {\"color\": \"#0072B2\"}, \"mode\": \"lines\", \"name\": \"11_amir_he_england_cricket\", \"type\": \"scatter\", \"x\": [\"2015-11-23T09:36:00\", \"2016-01-03T04:48:00\", \"2016-02-13T00:00:00\", \"2016-03-24T19:12:00\", \"2016-05-04T14:24:00\", \"2016-06-14T09:36:00\", \"2017-02-14T04:48:00\"], \"y\": [2, 5, 3, 2, 9, 17, 2]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 53</b><br>Words: lyon, test, lanka, pallekele, spinner\", \"<b>Topic 53</b><br>Words: pallekele, lanka, lyon, smith, nets\", \"<b>Topic 53</b><br>Words: lanka, pallekele, lyon, test, innings\"], \"marker\": {\"color\": \"#CC79A7\"}, \"mode\": \"lines\", \"name\": \"53_lanka_pallekele_lyon_test\", \"type\": \"scatter\", \"x\": [\"2015-11-23T09:36:00\", \"2016-06-14T09:36:00\", \"2016-07-25T04:48:00\"], \"y\": [1, 1, 12]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 5</b><br>Words: murray, federer, djokovic, nadal, slam\", \"<b>Topic 5</b><br>Words: nadal, djokovic, wimbledon, won, champion\", \"<b>Topic 5</b><br>Words: murray, djokovic, wimbledon, open, nadal\", \"<b>Topic 5</b><br>Words: federer, wimbledon, djokovic, slam, willis\", \"<b>Topic 5</b><br>Words: djokovic, wimbledon, federer, nadal, nishikori\"], \"marker\": {\"color\": \"#E69F00\"}, \"mode\": \"lines\", \"name\": \"5_murray_djokovic_federer_wimbledon\", \"type\": \"scatter\", \"x\": [\"2016-01-03T04:48:00\", \"2016-03-24T19:12:00\", \"2016-05-04T14:24:00\", \"2016-06-14T09:36:00\", \"2016-07-25T04:48:00\"], \"y\": [10, 5, 15, 12, 8]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 6</b><br>Words: karachi, qalandars, mohammad, lahore, wickets\", \"<b>Topic 6</b><br>Words: mohammad, peshawar, zalmi, karachi, islamabad\", \"<b>Topic 6</b><br>Words: fakhar, khan, punjab, ahmed, mohammad\", \"<b>Topic 6</b><br>Words: khan, zulfiqar, babar, mohammad, azhar\", \"<b>Topic 6</b><br>Words: licences, bidding, licence, subscribers, channels\"], \"marker\": {\"color\": \"#56B4E9\"}, \"mode\": \"lines\", \"name\": \"6_mohammad_zalmi_karachi_qalandars\", \"type\": \"scatter\", \"x\": [\"2016-01-03T04:48:00\", \"2016-02-13T00:00:00\", \"2016-03-24T19:12:00\", \"2016-06-14T09:36:00\", \"2016-10-14T19:12:00\"], \"y\": [18, 24, 3, 1, 1]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 7</b><br>Words: williams, konta, melbourne, slam, serve\", \"<b>Topic 7</b><br>Words: williams, serena, final, tournament, australian\", \"<b>Topic 7</b><br>Words: her, kerber, mirza, williams, final\", \"<b>Topic 7</b><br>Words: her, muguruza, williams, seed, serve\", \"<b>Topic 7</b><br>Words: her, williams, wimbledon, kerber, serena\"], \"marker\": {\"color\": \"#009E73\"}, \"mode\": \"lines\", \"name\": \"7_williams_radwanska_slam_australian\", \"type\": \"scatter\", \"x\": [\"2016-01-03T04:48:00\", \"2016-02-13T00:00:00\", \"2016-03-24T19:12:00\", \"2016-05-04T14:24:00\", \"2016-06-14T09:36:00\"], \"y\": [12, 7, 6, 11, 10]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 8</b><br>Words: zimbabwe, india, overs, kohli, ball\", \"<b>Topic 8</b><br>Words: zimbabwe, wickets, balls, kohli, india\", \"<b>Topic 8</b><br>Words: kohli, mumbai, overs, india, wickets\", \"<b>Topic 8</b><br>Words: chahal, kohli, wickets, picked, img\", \"<b>Topic 8</b><br>Words: kohli, ashwin, india, indies, overs\", \"<b>Topic 8</b><br>Words: innings, rahul, indies, kohli, wicket\"], \"marker\": {\"color\": \"#F0E442\"}, \"mode\": \"lines\", \"name\": \"8_kohli_india_overs_zimbabwe\", \"type\": \"scatter\", \"x\": [\"2016-01-03T04:48:00\", \"2016-02-13T00:00:00\", \"2016-03-24T19:12:00\", \"2016-05-04T14:24:00\", \"2016-06-14T09:36:00\", \"2016-07-25T04:48:00\"], \"y\": [8, 8, 12, 2, 11, 3]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 20</b><br>Words: pcb, cricket, shooting, khan, ahmed\", \"<b>Topic 20</b><br>Words: khan, coach, ahmed, selector, pakistan\", \"<b>Topic 20</b><br>Words: committee, coach, cricket, chief, selector\", \"<b>Topic 20</b><br>Words: cricket, khan, coach, mohammad, selector\", \"<b>Topic 20</b><br>Words: director, selector, chief, positions, appoint\", \"<b>Topic 20</b><br>Words: bowling, crowe, odi, cleared, coach\"], \"marker\": {\"color\": \"#D55E00\"}, \"mode\": \"lines\", \"name\": \"20_khan_cricket_coach_pakistan\", \"type\": \"scatter\", \"x\": [\"2016-01-03T04:48:00\", \"2016-02-13T00:00:00\", \"2016-03-24T19:12:00\", \"2016-05-04T14:24:00\", \"2016-06-14T09:36:00\", \"2016-07-25T04:48:00\"], \"y\": [4, 6, 13, 8, 1, 1]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 24</b><br>Words: afridi, shahid, shahzad, lahore, lied\", \"<b>Topic 24</b><br>Words: cricket, india, shahid, players, play\", \"<b>Topic 24</b><br>Words: cricket, captaincy, players, play, playing\", \"<b>Topic 24</b><br>Words: cricket, he, players, shoaib, dhoni\", \"<b>Topic 24</b><br>Words: afridi, cricket, he, shoaib, cricketers\"], \"marker\": {\"color\": \"#0072B2\"}, \"mode\": \"lines\", \"name\": \"24_afridi_cricket_team_players\", \"type\": \"scatter\", \"x\": [\"2016-01-03T04:48:00\", \"2016-02-13T00:00:00\", \"2016-03-24T19:12:00\", \"2016-05-04T14:24:00\", \"2016-06-14T09:36:00\"], \"y\": [2, 11, 8, 7, 2]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 28</b><br>Words: messi, argentina, barcelona, fifa, lionel\", \"<b>Topic 28</b><br>Words: messi, argentina, lionel, barcelona, chile\", \"<b>Topic 28</b><br>Words: messi, argentina, barcelona, chile, copa\", \"<b>Topic 28</b><br>Words: messi, argentina, barcelona, lionel, goal\"], \"marker\": {\"color\": \"#CC79A7\"}, \"mode\": \"lines\", \"name\": \"28_messi_argentina_barcelona_copa\", \"type\": \"scatter\", \"x\": [\"2016-01-03T04:48:00\", \"2016-03-24T19:12:00\", \"2016-05-04T14:24:00\", \"2016-06-14T09:36:00\"], \"y\": [3, 3, 8, 10]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 30</b><br>Words: zealand, williamson, mccullum, martin, balls\", \"<b>Topic 30</b><br>Words: australia, innings, caught, mitchell, latham\", \"<b>Topic 30</b><br>Words: williamson, zealand, mccullum, kane, brendon\", \"<b>Topic 30</b><br>Words: zealand, williamson, latham, caps, second\"], \"marker\": {\"color\": \"#E69F00\"}, \"mode\": \"lines\", \"name\": \"30_zealand_williamson_latham_innings\", \"type\": \"scatter\", \"x\": [\"2016-01-03T04:48:00\", \"2016-02-13T00:00:00\", \"2016-03-24T19:12:00\", \"2016-07-25T04:48:00\"], \"y\": [4, 7, 3, 9]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 31</b><br>Words: australia, khawaja, warner, rohit, watson\", \"<b>Topic 31</b><br>Words: smith, burns, rahman, hastings, khawaja\", \"<b>Topic 31</b><br>Words: australia, coach, maxwell, indies, warner\", \"<b>Topic 31</b><br>Words: australia, warner, indies, maxwell, odi\", \"<b>Topic 31</b><br>Words: australia, smith, start, barbados, indies\"], \"marker\": {\"color\": \"#56B4E9\"}, \"mode\": \"lines\", \"name\": \"31_australia_smith_warner_maxwell\", \"type\": \"scatter\", \"x\": [\"2016-01-03T04:48:00\", \"2016-02-13T00:00:00\", \"2016-03-24T19:12:00\", \"2016-05-04T14:24:00\", \"2016-06-14T09:36:00\"], \"y\": [9, 2, 6, 4, 1]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 34</b><br>Words: england, henry, australia, zealand, stokes\", \"<b>Topic 34</b><br>Words: england, moores, cricket, jordan, test\", \"<b>Topic 34</b><br>Words: england, anderson, stokes, headingley, knee\", \"<b>Topic 34</b><br>Words: england, anderson, ballance, cook, yorkshire\", \"<b>Topic 34</b><br>Words: test, england, stokes, series, trafford\"], \"marker\": {\"color\": \"#009E73\"}, \"mode\": \"lines\", \"name\": \"34_england_anderson_stokes_cook\", \"type\": \"scatter\", \"x\": [\"2016-01-03T04:48:00\", \"2016-03-24T19:12:00\", \"2016-05-04T14:24:00\", \"2016-06-14T09:36:00\", \"2016-07-25T04:48:00\"], \"y\": [2, 3, 3, 7, 6]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 35</b><br>Words: blackwell, canberra, women, australia, kaur\", \"<b>Topic 35</b><br>Words: women, overs, england, wicket, knight\", \"<b>Topic 35</b><br>Words: women, wickets, zealand, her, indies\", \"<b>Topic 35</b><br>Words: chelsea, lindahl, ladies, women, shot\", \"<b>Topic 35</b><br>Words: england, knight, her, overs, sciver\"], \"marker\": {\"color\": \"#F0E442\"}, \"mode\": \"lines\", \"name\": \"35_women_england_knight_overs\", \"type\": \"scatter\", \"x\": [\"2016-01-03T04:48:00\", \"2016-02-13T00:00:00\", \"2016-03-24T19:12:00\", \"2016-05-04T14:24:00\", \"2016-06-14T09:36:00\"], \"y\": [1, 7, 6, 1, 6]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 45</b><br>Words: event, ptf, trophy, peshawar, snooker\", \"<b>Topic 45</b><br>Words: tennis, players, championships, events, tournament\", \"<b>Topic 45</b><br>Words: cup, tennis, cricket, matches, tournament\", \"<b>Topic 45</b><br>Words: singles, ptf, tennis, getattribute, players\", \"<b>Topic 45</b><br>Words: cpl, games, franchise, florida, cricket\"], \"marker\": {\"color\": \"#D55E00\"}, \"mode\": \"lines\", \"name\": \"45_tennis_ptf_players_cricket\", \"type\": \"scatter\", \"x\": [\"2016-01-03T04:48:00\", \"2016-02-13T00:00:00\", \"2016-03-24T19:12:00\", \"2016-05-04T14:24:00\", \"2016-07-25T04:48:00\"], \"y\": [4, 5, 6, 1, 1]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 50</b><br>Words: sydney, abandoned, wet, ground, washed\", \"<b>Topic 50</b><br>Words: rain, ground, bangladesh, kolkata, ireland\", \"<b>Topic 50</b><br>Words: finch, warner, split, matches, spin\", \"<b>Topic 50</b><br>Words: rain, showers, weather, forecasts, sunshine\", \"<b>Topic 50</b><br>Words: jamaica, rain, interrupted, runs, indies\"], \"marker\": {\"color\": \"#0072B2\"}, \"mode\": \"lines\", \"name\": \"50_rain_ground_indies_sydney\", \"type\": \"scatter\", \"x\": [\"2016-01-03T04:48:00\", \"2016-02-13T00:00:00\", \"2016-03-24T19:12:00\", \"2016-05-04T14:24:00\", \"2016-07-25T04:48:00\"], \"y\": [5, 6, 1, 1, 2]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 55</b><br>Words: gladiators, quetta, wickets, ahmed, sharjah\", \"<b>Topic 55</b><br>Words: gladiators, quetta, zalmi, balls, runs\"], \"marker\": {\"color\": \"#CC79A7\"}, \"mode\": \"lines\", \"name\": \"55_gladiators_quetta_balls_zalmi\", \"type\": \"scatter\", \"x\": [\"2016-01-03T04:48:00\", \"2016-02-13T00:00:00\"], \"y\": [8, 5]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 57</b><br>Words: africa, england, balls, zealand, plessis\", \"<b>Topic 57</b><br>Words: balls, du, plessis, england, sixes\", \"<b>Topic 57</b><br>Words: sixes, fours, england, balls, buttler\"], \"marker\": {\"color\": \"#E69F00\"}, \"mode\": \"lines\", \"name\": \"57_africa_balls_england_sixes\", \"type\": \"scatter\", \"x\": [\"2016-01-03T04:48:00\", \"2016-02-13T00:00:00\", \"2016-03-24T19:12:00\"], \"y\": [4, 6, 2]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 62</b><br>Words: guerrero, wbc, welterweight, fight, garcia\", \"<b>Topic 62</b><br>Words: alvarez, mayweather, fight, welterweight, khan\", \"<b>Topic 62</b><br>Words: khan, boxing, fight, wbc, boxer\", \"<b>Topic 62</b><br>Words: fight, boxing, boxer, mayweather, wbc\", \"<b>Topic 62</b><br>Words: pacquiao, bradley, fight, welterweight, boxing\"], \"marker\": {\"color\": \"#56B4E9\"}, \"mode\": \"lines\", \"name\": \"62_khan_fight_boxing_wbc\", \"type\": \"scatter\", \"x\": [\"2016-01-03T04:48:00\", \"2016-03-24T19:12:00\", \"2016-05-04T14:24:00\", \"2016-06-14T09:36:00\", \"2016-07-25T04:48:00\"], \"y\": [1, 1, 5, 2, 1]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 25</b><br>Words: rashford, manchester, arsenal, midtjylland, club\", \"<b>Topic 25</b><br>Words: football, manchester, united, spanish, spain\", \"<b>Topic 25</b><br>Words: mourinho, league, manchester, club, manager\", \"<b>Topic 25</b><br>Words: mourinho, manchester, rooney, he, ibrahimovic\", \"<b>Topic 25</b><br>Words: pounds, manchester, mourinho, arsenal, chelsea\"], \"marker\": {\"color\": \"#009E73\"}, \"mode\": \"lines\", \"name\": \"25_mourinho_united_manchester_league\", \"type\": \"scatter\", \"x\": [\"2016-02-13T00:00:00\", \"2016-03-24T19:12:00\", \"2016-05-04T14:24:00\", \"2016-06-14T09:36:00\", \"2016-07-25T04:48:00\"], \"y\": [1, 1, 14, 7, 2]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 26</b><br>Words: sharapova, doping, meldonium, tennis, wada\", \"<b>Topic 26</b><br>Words: sharapova, drug, meldonium, doping, tested\", \"<b>Topic 26</b><br>Words: doping, sharapova, meldonium, tennis, tested\", \"<b>Topic 26</b><br>Words: sharapova, doping, meldonium, banned, anti\", \"<b>Topic 26</b><br>Words: inderjeet, tested, doping, nada, test\"], \"marker\": {\"color\": \"#F0E442\"}, \"mode\": \"lines\", \"name\": \"26_sharapova_doping_meldonium_banned\", \"type\": \"scatter\", \"x\": [\"2016-02-13T00:00:00\", \"2016-03-24T19:12:00\", \"2016-05-04T14:24:00\", \"2016-06-14T09:36:00\", \"2016-07-25T04:48:00\"], \"y\": [5, 4, 8, 7, 1]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 38</b><br>Words: lanka, wickets, indies, spinner, windies\", \"<b>Topic 38</b><br>Words: indies, brathwaite, wickets, wicket, balls\", \"<b>Topic 38</b><br>Words: indies, africans, villiers, africa, wickets\", \"<b>Topic 38</b><br>Words: indies, brathwaite, wicket, innings, overs\", \"<b>Topic 38</b><br>Words: indies, innings, brathwaite, chase, off\"], \"marker\": {\"color\": \"#D55E00\"}, \"mode\": \"lines\", \"name\": \"38_indies_brathwaite_wickets_wicket\", \"type\": \"scatter\", \"x\": 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banners, globalisation, consumers\", \"<b>Topic 4</b><br>Words: restaurants, restaurant, chef, french, savoy\"], \"marker\": {\"color\": \"#CC79A7\"}, \"mode\": \"lines\", \"name\": \"4_france_germany_euro_marseille\", \"type\": \"scatter\", \"x\": [\"2016-03-24T19:12:00\", \"2016-05-04T14:24:00\", \"2016-06-14T09:36:00\", \"2016-07-25T04:48:00\", \"2016-09-04T00:00:00\", \"2016-11-24T14:24:00\"], \"y\": [1, 16, 42, 1, 1, 1]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 21</b><br>Words: olympic, brazil, torch, brazilian, ferrari\", \"<b>Topic 21</b><br>Words: olympic, everest, olympics, climbers, brazil\", \"<b>Topic 21</b><br>Words: rio, olympic, brazil, olympics, janeiro\", \"<b>Topic 21</b><br>Words: rio, olympic, torch, brazil, janeiro\"], \"marker\": {\"color\": \"#E69F00\"}, \"mode\": \"lines\", \"name\": \"21_rio_olympic_brazil_janeiro\", \"type\": \"scatter\", \"x\": [\"2016-03-24T19:12:00\", \"2016-05-04T14:24:00\", \"2016-06-14T09:36:00\", \"2016-07-25T04:48:00\"], \"y\": [4, 5, 13, 9]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 27</b><br>Words: ronaldo, portugal, madrid, barcelona, cristiano\", \"<b>Topic 27</b><br>Words: ronaldo, portugal, madrid, cristiano, france\", \"<b>Topic 27</b><br>Words: ronaldo, portugal, france, cristiano, madrid\"], \"marker\": {\"color\": \"#56B4E9\"}, \"mode\": \"lines\", \"name\": \"27_ronaldo_portugal_cristiano_france\", \"type\": \"scatter\", \"x\": [\"2016-03-24T19:12:00\", \"2016-05-04T14:24:00\", \"2016-06-14T09:36:00\"], \"y\": [3, 7, 14]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 39</b><br>Words: chile, colombia, concacaf, uruguay, mexico\", \"<b>Topic 39</b><br>Words: mexico, uruguay, goal, venezuela, colombia\", \"<b>Topic 39</b><br>Words: colombia, chile, argentina, vargas, ecuador\", \"<b>Topic 39</b><br>Words: delgado, mexican, rio, mexico, boxing\"], \"marker\": {\"color\": \"#009E73\"}, \"mode\": \"lines\", \"name\": \"39_colombia_chile_venezuela_uruguay\", \"type\": \"scatter\", \"x\": [\"2016-03-24T19:12:00\", \"2016-05-04T14:24:00\", \"2016-06-14T09:36:00\", \"2016-07-25T04:48:00\"], \"y\": [1, 7, 10, 1]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 29</b><br>Words: dollar, recruitment, debt, jobs, brexit\", \"<b>Topic 29</b><br>Words: pound, sterling, brexit, uk, britain\", \"<b>Topic 29</b><br>Words: jobs, brexit, britain, uk, economy\", \"<b>Topic 29</b><br>Words: pound, ftse, dax, sterling, britain\"], \"marker\": {\"color\": \"#F0E442\"}, \"mode\": \"lines\", \"name\": \"29_brexit_pound_britain_uk\", \"type\": \"scatter\", \"x\": [\"2016-05-04T14:24:00\", \"2016-06-14T09:36:00\", \"2016-07-25T04:48:00\", \"2016-09-04T00:00:00\"], \"y\": [3, 9, 10, 1]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 32</b><br>Words: dates, dagger, products, cosmetics, dubai\", \"<b>Topic 32</b><br>Words: sweets, sale, jewellery, sell, customers\", \"<b>Topic 32</b><br>Words: cosmetics, korea, korean, products, brands\", \"<b>Topic 32</b><br>Words: deals, festival, color, gosf, brands\", \"<b>Topic 32</b><br>Words: products, customers, discounts, cosmetics, deals\"], \"marker\": {\"color\": \"#D55E00\"}, \"mode\": \"lines\", \"name\": \"32_cosmetics_korea_korean_products\", \"type\": \"scatter\", \"x\": [\"2016-05-04T14:24:00\", \"2016-06-14T09:36:00\", \"2016-07-25T04:48:00\", \"2016-09-04T00:00:00\", \"2016-10-14T19:12:00\"], \"y\": [3, 4, 7, 6, 2]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 46</b><br>Words: ali, boxing, muhammad, his, he\", \"<b>Topic 46</b><br>Words: ali, boxing, namesake, strongtwo, heavyweight\"], \"marker\": {\"color\": \"#0072B2\"}, \"mode\": \"lines\", \"name\": \"46_ali_boxing_muhammad_his\", \"type\": \"scatter\", \"x\": [\"2016-05-04T14:24:00\", \"2016-07-25T04:48:00\"], \"y\": [16, 1]}, {\"hoverinfo\": \"text\", \"hovertext\": [\"<b>Topic 56</b><br>Words: cook, woakes, amir, innings, ali\", \"<b>Topic 56</b><br>Words: england, root, test, hales, woakes\"], \"marker\": 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\"white\", \"showlakes\": true, \"showland\": true, \"subunitcolor\": \"white\"}, \"hoverlabel\": {\"align\": \"left\"}, \"hovermode\": \"closest\", \"mapbox\": {\"style\": \"light\"}, \"paper_bgcolor\": \"white\", \"plot_bgcolor\": \"white\", \"polar\": {\"angularaxis\": {\"gridcolor\": \"rgb(232,232,232)\", \"linecolor\": \"rgb(36,36,36)\", \"showgrid\": false, \"showline\": true, \"ticks\": \"outside\"}, \"bgcolor\": \"white\", \"radialaxis\": {\"gridcolor\": \"rgb(232,232,232)\", \"linecolor\": \"rgb(36,36,36)\", \"showgrid\": false, \"showline\": true, \"ticks\": \"outside\"}}, \"scene\": {\"xaxis\": {\"backgroundcolor\": \"white\", \"gridcolor\": \"rgb(232,232,232)\", \"gridwidth\": 2, \"linecolor\": \"rgb(36,36,36)\", \"showbackground\": true, \"showgrid\": false, \"showline\": true, \"ticks\": \"outside\", \"zeroline\": false, \"zerolinecolor\": \"rgb(36,36,36)\"}, \"yaxis\": {\"backgroundcolor\": \"white\", \"gridcolor\": \"rgb(232,232,232)\", \"gridwidth\": 2, \"linecolor\": \"rgb(36,36,36)\", \"showbackground\": true, \"showgrid\": false, \"showline\": true, \"ticks\": \"outside\", \"zeroline\": false, \"zerolinecolor\": \"rgb(36,36,36)\"}, \"zaxis\": {\"backgroundcolor\": \"white\", \"gridcolor\": \"rgb(232,232,232)\", \"gridwidth\": 2, \"linecolor\": \"rgb(36,36,36)\", \"showbackground\": true, \"showgrid\": false, \"showline\": true, \"ticks\": \"outside\", \"zeroline\": false, \"zerolinecolor\": \"rgb(36,36,36)\"}}, \"shapedefaults\": {\"fillcolor\": \"black\", \"line\": {\"width\": 0}, \"opacity\": 0.3}, \"ternary\": {\"aaxis\": {\"gridcolor\": \"rgb(232,232,232)\", \"linecolor\": \"rgb(36,36,36)\", \"showgrid\": false, \"showline\": true, \"ticks\": \"outside\"}, \"baxis\": {\"gridcolor\": \"rgb(232,232,232)\", \"linecolor\": \"rgb(36,36,36)\", \"showgrid\": false, \"showline\": true, \"ticks\": \"outside\"}, \"bgcolor\": \"white\", \"caxis\": {\"gridcolor\": \"rgb(232,232,232)\", \"linecolor\": \"rgb(36,36,36)\", \"showgrid\": false, \"showline\": true, \"ticks\": \"outside\"}}, \"title\": {\"x\": 0.05}, \"xaxis\": {\"automargin\": true, \"gridcolor\": \"rgb(232,232,232)\", \"linecolor\": \"rgb(36,36,36)\", \"showgrid\": false, \"showline\": true, \"ticks\": \"outside\", \"title\": {\"standoff\": 15}, \"zeroline\": false, \"zerolinecolor\": \"rgb(36,36,36)\"}, \"yaxis\": {\"automargin\": true, \"gridcolor\": \"rgb(232,232,232)\", \"linecolor\": \"rgb(36,36,36)\", \"showgrid\": false, \"showline\": true, \"ticks\": \"outside\", \"title\": {\"standoff\": 15}, \"zeroline\": false, \"zerolinecolor\": \"rgb(36,36,36)\"}}}, \"title\": {\"font\": {\"color\": \"Black\", \"size\": 22}, \"text\": \"<b>Topics over Time\", \"x\": 0.4, \"xanchor\": \"center\", \"y\": 0.95, \"yanchor\": \"top\"}, \"width\": 1250, \"xaxis\": {\"showgrid\": true}, \"yaxis\": {\"showgrid\": true, \"title\": {\"text\": \"Frequency\"}}},                        {\"responsive\": true}                    ).then(function(){\n",
              "                            \n",
              "var gd = document.getElementById('29839413-46e4-4b2a-b37e-27633e7411fc');\n",
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              "            Plotly.purge(gd);\n",
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              "var outputEl = gd.closest('.output');\n",
              "if (outputEl) {{\n",
              "    x.observe(outputEl, {childList: true});\n",
              "}}\n",
              "\n",
              "                        })                };                            </script>        </div>\n",
              "</body>\n",
              "</html>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 422
        },
        "id": "vTVAhcb4Ujrg",
        "outputId": "77e8b034-9f99-4151-a4b2-fa4cf8467681"
      },
      "source": [
        "x = bert_topic_model.get_topic_table()\n",
        "x"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
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              "\n",
              "    .dataframe tbody tr th {\n",
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              "\n",
              "    .dataframe thead th {\n",
              "        text-align: right;\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Topic 1</th>\n",
              "      <th>Topic 2</th>\n",
              "      <th>Topic 3</th>\n",
              "      <th>Topic 4</th>\n",
              "      <th>Topic 5</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>48</td>\n",
              "      <td>43</td>\n",
              "      <td>12</td>\n",
              "      <td>52</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
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              "      <td>0</td>\n",
              "      <td>14</td>\n",
              "      <td>19</td>\n",
              "      <td>32</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>0</td>\n",
              "      <td>17</td>\n",
              "      <td>2</td>\n",
              "      <td>32</td>\n",
              "      <td>19</td>\n",
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              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>0</td>\n",
              "      <td>32</td>\n",
              "      <td>2</td>\n",
              "      <td>50</td>\n",
              "      <td>19</td>\n",
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              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>1</td>\n",
              "      <td>10</td>\n",
              "      <td>22</td>\n",
              "      <td>47</td>\n",
              "      <td>12</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2687</th>\n",
              "      <td>43</td>\n",
              "      <td>52</td>\n",
              "      <td>42</td>\n",
              "      <td>2</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2688</th>\n",
              "      <td>2</td>\n",
              "      <td>6</td>\n",
              "      <td>15</td>\n",
              "      <td>42</td>\n",
              "      <td>3</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2689</th>\n",
              "      <td>13</td>\n",
              "      <td>43</td>\n",
              "      <td>12</td>\n",
              "      <td>25</td>\n",
              "      <td>4</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2690</th>\n",
              "      <td>2</td>\n",
              "      <td>60</td>\n",
              "      <td>14</td>\n",
              "      <td>0</td>\n",
              "      <td>40</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2691</th>\n",
              "      <td>44</td>\n",
              "      <td>60</td>\n",
              "      <td>2</td>\n",
              "      <td>45</td>\n",
              "      <td>6</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>2692 rows × 5 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "      Topic 1  Topic 2  Topic 3  Topic 4  Topic 5\n",
              "0          48       43       12       52        6\n",
              "1           2        0       14       19       32\n",
              "2           0       17        2       32       19\n",
              "3           0       32        2       50       19\n",
              "4           1       10       22       47       12\n",
              "...       ...      ...      ...      ...      ...\n",
              "2687       43       52       42        2        6\n",
              "2688        2        6       15       42        3\n",
              "2689       13       43       12       25        4\n",
              "2690        2       60       14        0       40\n",
              "2691       44       60        2       45        6\n",
              "\n",
              "[2692 rows x 5 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "xvrDbEJfkKrM"
      },
      "source": [
        "###3.2. Topic Modelling With LDA"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "MowHS6gjrb65",
        "outputId": "6a8189d3-a370-4a25-ce13-777b0960ebdd"
      },
      "source": [
        "lda_topic_model = con.tm_lda()"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[nltk_data] Downloading package stopwords to /root/nltk_data...\n",
            "[nltk_data]   Package stopwords is already up-to-date!\n",
            "Beginning vecorization\n",
            "Vecorization complete\n",
            "Beginning grid search\n",
            "Completed grid search\n",
            "Constructing LDA\n",
            "Competed LDA\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 595
        },
        "id": "xzspbvveITXP",
        "outputId": "704b92af-099f-405e-857f-542769ce2b5b"
      },
      "source": [
        "lda_topic_model.get_dominant_topics()"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/html": [
              "<div>\n",
              "<style scoped>\n",
              "    .dataframe tbody tr th:only-of-type {\n",
              "        vertical-align: middle;\n",
              "    }\n",
              "\n",
              "    .dataframe tbody tr th {\n",
              "        vertical-align: top;\n",
              "    }\n",
              "\n",
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              "        text-align: right;\n",
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              "</style>\n",
              "<table border=\"1\" class=\"dataframe\">\n",
              "  <thead>\n",
              "    <tr style=\"text-align: right;\">\n",
              "      <th></th>\n",
              "      <th>Document_No</th>\n",
              "      <th>Dominant_Topic</th>\n",
              "      <th>Topic_Perc_Contrib</th>\n",
              "      <th>Keywords</th>\n",
              "      <th>Text</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>0</td>\n",
              "      <td>2.0</td>\n",
              "      <td>0.7252</td>\n",
              "      <td>country, project, company, year, economic, gov...</td>\n",
              "      <td>[government, decide, bring, public, transport,...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>1</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.6976</td>\n",
              "      <td>percent, oil, market, price, cut, high, year, ...</td>\n",
              "      <td>[hong_kong, asian, market, start, upswe, limit...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>2</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.5579</td>\n",
              "      <td>percent, oil, market, price, cut, high, year, ...</td>\n",
              "      <td>[share, open, percent, low, follow, tepid, lea...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>3</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.6312</td>\n",
              "      <td>percent, oil, market, price, cut, high, year, ...</td>\n",
              "      <td>[hong_kong, asian, market, tumble, follow, pai...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>4</td>\n",
              "      <td>1.0</td>\n",
              "      <td>0.7156</td>\n",
              "      <td>percent, oil, market, price, cut, high, year, ...</td>\n",
              "      <td>[oil, price, slip, barrel, first, time, year, ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>...</th>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "      <td>...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2687</th>\n",
              "      <td>2687</td>\n",
              "      <td>2.0</td>\n",
              "      <td>0.5166</td>\n",
              "      <td>country, project, company, year, economic, gov...</td>\n",
              "      <td>[begin, implement, ban, laptop, tablet, busy, ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2688</th>\n",
              "      <td>2688</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.4764</td>\n",
              "      <td>year, strong, include, time, world, team, peop...</td>\n",
              "      <td>[strong, former, stand, test, time, country, l...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2689</th>\n",
              "      <td>2689</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.3571</td>\n",
              "      <td>year, strong, include, time, world, team, peop...</td>\n",
              "      <td>[ground, fleet, car, pende, investigation, cra...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2690</th>\n",
              "      <td>2690</td>\n",
              "      <td>2.0</td>\n",
              "      <td>0.6134</td>\n",
              "      <td>country, project, company, year, economic, gov...</td>\n",
              "      <td>[strong, plan, finance, asian, infrastructure,...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2691</th>\n",
              "      <td>2691</td>\n",
              "      <td>0.0</td>\n",
              "      <td>0.6696</td>\n",
              "      <td>year, strong, include, time, world, team, peop...</td>\n",
              "      <td>[strong, base, technology, incubator, organize...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "<p>2692 rows × 5 columns</p>\n",
              "</div>"
            ],
            "text/plain": [
              "      Document_No  ...                                               Text\n",
              "0               0  ...  [government, decide, bring, public, transport,...\n",
              "1               1  ...  [hong_kong, asian, market, start, upswe, limit...\n",
              "2               2  ...  [share, open, percent, low, follow, tepid, lea...\n",
              "3               3  ...  [hong_kong, asian, market, tumble, follow, pai...\n",
              "4               4  ...  [oil, price, slip, barrel, first, time, year, ...\n",
              "...           ...  ...                                                ...\n",
              "2687         2687  ...  [begin, implement, ban, laptop, tablet, busy, ...\n",
              "2688         2688  ...  [strong, former, stand, test, time, country, l...\n",
              "2689         2689  ...  [ground, fleet, car, pende, investigation, cra...\n",
              "2690         2690  ...  [strong, plan, finance, asian, infrastructure,...\n",
              "2691         2691  ...  [strong, base, technology, incubator, organize...\n",
              "\n",
              "[2692 rows x 5 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 11
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "udUtPpCPIwIS",
        "outputId": "6ad4c11c-4dc7-4dfd-d451-f5bfc1f89476"
      },
      "source": [
        "for i in range(4):\n",
        "\n",
        "  lda_topic_model.get_topic_word_cloud(i)\n",
        "\n",
        "# lda_topic_model.get_topic_word_cloud(1)"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 607
        },
        "id": "qg0wf_r-I0Hw",
        "outputId": "c2fc6f84-bc8d-421e-a83d-5277c4c97e50"
      },
      "source": [
        "lda_topic_model.get_topic_word_dist(1)"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 720x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 461
        },
        "id": "dQ0f9TVwJRQ3",
        "outputId": "46cc3096-e7dd-44c3-b4d1-3ef2985b6e47"
      },
      "source": [
        "lda_topic_model.get_sentence_colors(0,10)"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 3200x1520 with 10 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 0 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 899
        },
        "id": "epnop7axJYiT",
        "outputId": "75dffb8b-bbc5-4e96-af32-1f64517d6cc8"
      },
      "source": [
        "lda_topic_model.get_sne_cluster()"
      ],
      "execution_count": 15,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[t-SNE] Computing 91 nearest neighbors...\n",
            "[t-SNE] Indexed 2672 samples in 0.002s...\n",
            "[t-SNE] Computed neighbors for 2672 samples in 0.052s...\n",
            "[t-SNE] Computed conditional probabilities for sample 1000 / 2672\n",
            "[t-SNE] Computed conditional probabilities for sample 2000 / 2672\n",
            "[t-SNE] Computed conditional probabilities for sample 2672 / 2672\n",
            "[t-SNE] Mean sigma: 0.034182\n",
            "[t-SNE] KL divergence after 250 iterations with early exaggeration: 61.258781\n",
            "[t-SNE] KL divergence after 1000 iterations: 0.635544\n"
          ],
          "name": "stdout"
        },
        {
          "output_type": "display_data",
          "data": {
            "application/javascript": [
              "\n",
              "(function(root) {\n",
              "  function now() {\n",
              "    return new Date();\n",
              "  }\n",
              "\n",
              "  var force = true;\n",
              "\n",
              "  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n",
              "    root._bokeh_onload_callbacks = [];\n",
              "    root._bokeh_is_loading = undefined;\n",
              "  }\n",
              "\n",
              "  var JS_MIME_TYPE = 'application/javascript';\n",
              "  var HTML_MIME_TYPE = 'text/html';\n",
              "  var EXEC_MIME_TYPE = 'application/vnd.bokehjs_exec.v0+json';\n",
              "  var CLASS_NAME = 'output_bokeh rendered_html';\n",
              "\n",
              "  /**\n",
              "   * Render data to the DOM node\n",
              "   */\n",
              "  function render(props, node) {\n",
              "    var script = document.createElement(\"script\");\n",
              "    node.appendChild(script);\n",
              "  }\n",
              "\n",
              "  /**\n",
              "   * Handle when an output is cleared or removed\n",
              "   */\n",
              "  function handleClearOutput(event, handle) {\n",
              "    var cell = handle.cell;\n",
              "\n",
              "    var id = cell.output_area._bokeh_element_id;\n",
              "    var server_id = cell.output_area._bokeh_server_id;\n",
              "    // Clean up Bokeh references\n",
              "    if (id != null && id in Bokeh.index) {\n",
              "      Bokeh.index[id].model.document.clear();\n",
              "      delete Bokeh.index[id];\n",
              "    }\n",
              "\n",
              "    if (server_id !== undefined) {\n",
              "      // Clean up Bokeh references\n",
              "      var cmd = \"from bokeh.io.state import curstate; print(curstate().uuid_to_server['\" + server_id + \"'].get_sessions()[0].document.roots[0]._id)\";\n",
              "      cell.notebook.kernel.execute(cmd, {\n",
              "        iopub: {\n",
              "          output: function(msg) {\n",
              "            var id = msg.content.text.trim();\n",
              "            if (id in Bokeh.index) {\n",
              "              Bokeh.index[id].model.document.clear();\n",
              "              delete Bokeh.index[id];\n",
              "            }\n",
              "          }\n",
              "        }\n",
              "      });\n",
              "      // Destroy server and session\n",
              "      var cmd = \"import bokeh.io.notebook as ion; ion.destroy_server('\" + server_id + \"')\";\n",
              "      cell.notebook.kernel.execute(cmd);\n",
              "    }\n",
              "  }\n",
              "\n",
              "  /**\n",
              "   * Handle when a new output is added\n",
              "   */\n",
              "  function handleAddOutput(event, handle) {\n",
              "    var output_area = handle.output_area;\n",
              "    var output = handle.output;\n",
              "\n",
              "    // limit handleAddOutput to display_data with EXEC_MIME_TYPE content only\n",
              "    if ((output.output_type != \"display_data\") || (!Object.prototype.hasOwnProperty.call(output.data, EXEC_MIME_TYPE))) {\n",
              "      return\n",
              "    }\n",
              "\n",
              "    var toinsert = output_area.element.find(\".\" + CLASS_NAME.split(' ')[0]);\n",
              "\n",
              "    if (output.metadata[EXEC_MIME_TYPE][\"id\"] !== undefined) {\n",
              "      toinsert[toinsert.length - 1].firstChild.textContent = output.data[JS_MIME_TYPE];\n",
              "      // store reference to embed id on output_area\n",
              "      output_area._bokeh_element_id = output.metadata[EXEC_MIME_TYPE][\"id\"];\n",
              "    }\n",
              "    if (output.metadata[EXEC_MIME_TYPE][\"server_id\"] !== undefined) {\n",
              "      var bk_div = document.createElement(\"div\");\n",
              "      bk_div.innerHTML = output.data[HTML_MIME_TYPE];\n",
              "      var script_attrs = bk_div.children[0].attributes;\n",
              "      for (var i = 0; i < script_attrs.length; i++) {\n",
              "        toinsert[toinsert.length - 1].firstChild.setAttribute(script_attrs[i].name, script_attrs[i].value);\n",
              "        toinsert[toinsert.length - 1].firstChild.textContent = bk_div.children[0].textContent\n",
              "      }\n",
              "      // store reference to server id on output_area\n",
              "      output_area._bokeh_server_id = output.metadata[EXEC_MIME_TYPE][\"server_id\"];\n",
              "    }\n",
              "  }\n",
              "\n",
              "  function register_renderer(events, OutputArea) {\n",
              "\n",
              "    function append_mime(data, metadata, element) {\n",
              "      // create a DOM node to render to\n",
              "      var toinsert = this.create_output_subarea(\n",
              "        metadata,\n",
              "        CLASS_NAME,\n",
              "        EXEC_MIME_TYPE\n",
              "      );\n",
              "      this.keyboard_manager.register_events(toinsert);\n",
              "      // Render to node\n",
              "      var props = {data: data, metadata: metadata[EXEC_MIME_TYPE]};\n",
              "      render(props, toinsert[toinsert.length - 1]);\n",
              "      element.append(toinsert);\n",
              "      return toinsert\n",
              "    }\n",
              "\n",
              "    /* Handle when an output is cleared or removed */\n",
              "    events.on('clear_output.CodeCell', handleClearOutput);\n",
              "    events.on('delete.Cell', handleClearOutput);\n",
              "\n",
              "    /* Handle when a new output is added */\n",
              "    events.on('output_added.OutputArea', handleAddOutput);\n",
              "\n",
              "    /**\n",
              "     * Register the mime type and append_mime function with output_area\n",
              "     */\n",
              "    OutputArea.prototype.register_mime_type(EXEC_MIME_TYPE, append_mime, {\n",
              "      /* Is output safe? */\n",
              "      safe: true,\n",
              "      /* Index of renderer in `output_area.display_order` */\n",
              "      index: 0\n",
              "    });\n",
              "  }\n",
              "\n",
              "  // register the mime type if in Jupyter Notebook environment and previously unregistered\n",
              "  if (root.Jupyter !== undefined) {\n",
              "    var events = require('base/js/events');\n",
              "    var OutputArea = require('notebook/js/outputarea').OutputArea;\n",
              "\n",
              "    if (OutputArea.prototype.mime_types().indexOf(EXEC_MIME_TYPE) == -1) {\n",
              "      register_renderer(events, OutputArea);\n",
              "    }\n",
              "  }\n",
              "\n",
              "  \n",
              "  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n",
              "    root._bokeh_timeout = Date.now() + 5000;\n",
              "    root._bokeh_failed_load = false;\n",
              "  }\n",
              "\n",
              "  var NB_LOAD_WARNING = {'data': {'text/html':\n",
              "     \"<div style='background-color: #fdd'>\\n\"+\n",
              "     \"<p>\\n\"+\n",
              "     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n",
              "     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n",
              "     \"</p>\\n\"+\n",
              "     \"<ul>\\n\"+\n",
              "     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n",
              "     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n",
              "     \"</ul>\\n\"+\n",
              "     \"<code>\\n\"+\n",
              "     \"from bokeh.resources import INLINE\\n\"+\n",
              "     \"output_notebook(resources=INLINE)\\n\"+\n",
              "     \"</code>\\n\"+\n",
              "     \"</div>\"}};\n",
              "\n",
              "  function display_loaded() {\n",
              "    var el = document.getElementById(null);\n",
              "    if (el != null) {\n",
              "      el.textContent = \"BokehJS is loading...\";\n",
              "    }\n",
              "    if (root.Bokeh !== undefined) {\n",
              "      if (el != null) {\n",
              "        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n",
              "      }\n",
              "    } else if (Date.now() < root._bokeh_timeout) {\n",
              "      setTimeout(display_loaded, 100)\n",
              "    }\n",
              "  }\n",
              "\n",
              "\n",
              "  function run_callbacks() {\n",
              "    try {\n",
              "      root._bokeh_onload_callbacks.forEach(function(callback) {\n",
              "        if (callback != null)\n",
              "          callback();\n",
              "      });\n",
              "    } finally {\n",
              "      delete root._bokeh_onload_callbacks\n",
              "    }\n",
              "    console.debug(\"Bokeh: all callbacks have finished\");\n",
              "  }\n",
              "\n",
              "  function load_libs(css_urls, js_urls, callback) {\n",
              "    if (css_urls == null) css_urls = [];\n",
              "    if (js_urls == null) js_urls = [];\n",
              "\n",
              "    root._bokeh_onload_callbacks.push(callback);\n",
              "    if (root._bokeh_is_loading > 0) {\n",
              "      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n",
              "      return null;\n",
              "    }\n",
              "    if (js_urls == null || js_urls.length === 0) {\n",
              "      run_callbacks();\n",
              "      return null;\n",
              "    }\n",
              "    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n",
              "    root._bokeh_is_loading = css_urls.length + js_urls.length;\n",
              "\n",
              "    function on_load() {\n",
              "      root._bokeh_is_loading--;\n",
              "      if (root._bokeh_is_loading === 0) {\n",
              "        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n",
              "        run_callbacks()\n",
              "      }\n",
              "    }\n",
              "\n",
              "    function on_error(url) {\n",
              "      console.error(\"failed to load \" + url);\n",
              "    }\n",
              "\n",
              "    for (let i = 0; i < css_urls.length; i++) {\n",
              "      const url = css_urls[i];\n",
              "      const element = document.createElement(\"link\");\n",
              "      element.onload = on_load;\n",
              "      element.onerror = on_error.bind(null, url);\n",
              "      element.rel = \"stylesheet\";\n",
              "      element.type = \"text/css\";\n",
              "      element.href = url;\n",
              "      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n",
              "      document.body.appendChild(element);\n",
              "    }\n",
              "\n",
              "    const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.3.3.min.js\": \"dM3QQsP+wXdHg42wTqW85BjZQdLNNIXqlPw/BgKoExPmTG7ZLML4EGqLMfqHT6ON\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.3.3.min.js\": \"8x57I4YuIfu8XyZfFo0XVr2WAT8EK4rh/uDe3wF7YuW2FNUSNEpJbsPaB1nJ2fz2\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.3.3.min.js\": \"3QTqdz9LyAm2i0sG5XTePsHec3UHWwVsrOL68SYRoAXsafvfAyqtQ+h440+qIBhS\"};\n",
              "\n",
              "    for (let i = 0; i < js_urls.length; i++) {\n",
              "      const url = js_urls[i];\n",
              "      const element = document.createElement('script');\n",
              "      element.onload = on_load;\n",
              "      element.onerror = on_error.bind(null, url);\n",
              "      element.async = false;\n",
              "      element.src = url;\n",
              "      if (url in hashes) {\n",
              "        element.crossOrigin = \"anonymous\";\n",
              "        element.integrity = \"sha384-\" + hashes[url];\n",
              "      }\n",
              "      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n",
              "      document.head.appendChild(element);\n",
              "    }\n",
              "  };\n",
              "\n",
              "  function inject_raw_css(css) {\n",
              "    const element = document.createElement(\"style\");\n",
              "    element.appendChild(document.createTextNode(css));\n",
              "    document.body.appendChild(element);\n",
              "  }\n",
              "\n",
              "  \n",
              "  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.3.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.3.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.3.3.min.js\"];\n",
              "  var css_urls = [];\n",
              "  \n",
              "\n",
              "  var inline_js = [\n",
              "    function(Bokeh) {\n",
              "      Bokeh.set_log_level(\"info\");\n",
              "    },\n",
              "    function(Bokeh) {\n",
              "    \n",
              "    \n",
              "    }\n",
              "  ];\n",
              "\n",
              "  function run_inline_js() {\n",
              "    \n",
              "    if (root.Bokeh !== undefined || force === true) {\n",
              "      \n",
              "    for (var i = 0; i < inline_js.length; i++) {\n",
              "      inline_js[i].call(root, root.Bokeh);\n",
              "    }\n",
              "    } else if (Date.now() < root._bokeh_timeout) {\n",
              "      setTimeout(run_inline_js, 100);\n",
              "    } else if (!root._bokeh_failed_load) {\n",
              "      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n",
              "      root._bokeh_failed_load = true;\n",
              "    } else if (force !== true) {\n",
              "      var cell = $(document.getElementById(null)).parents('.cell').data().cell;\n",
              "      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n",
              "    }\n",
              "\n",
              "  }\n",
              "\n",
              "  if (root._bokeh_is_loading === 0) {\n",
              "    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n",
              "    run_inline_js();\n",
              "  } else {\n",
              "    load_libs(css_urls, js_urls, function() {\n",
              "      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n",
              "      run_inline_js();\n",
              "    });\n",
              "  }\n",
              "}(window));"
            ],
            "application/vnd.bokehjs_load.v0+json": "\n(function(root) {\n  function now() {\n    return new Date();\n  }\n\n  var force = true;\n\n  if (typeof root._bokeh_onload_callbacks === \"undefined\" || force === true) {\n    root._bokeh_onload_callbacks = [];\n    root._bokeh_is_loading = undefined;\n  }\n\n  \n\n  \n  if (typeof (root._bokeh_timeout) === \"undefined\" || force === true) {\n    root._bokeh_timeout = Date.now() + 5000;\n    root._bokeh_failed_load = false;\n  }\n\n  var NB_LOAD_WARNING = {'data': {'text/html':\n     \"<div style='background-color: #fdd'>\\n\"+\n     \"<p>\\n\"+\n     \"BokehJS does not appear to have successfully loaded. If loading BokehJS from CDN, this \\n\"+\n     \"may be due to a slow or bad network connection. Possible fixes:\\n\"+\n     \"</p>\\n\"+\n     \"<ul>\\n\"+\n     \"<li>re-rerun `output_notebook()` to attempt to load from CDN again, or</li>\\n\"+\n     \"<li>use INLINE resources instead, as so:</li>\\n\"+\n     \"</ul>\\n\"+\n     \"<code>\\n\"+\n     \"from bokeh.resources import INLINE\\n\"+\n     \"output_notebook(resources=INLINE)\\n\"+\n     \"</code>\\n\"+\n     \"</div>\"}};\n\n  function display_loaded() {\n    var el = document.getElementById(null);\n    if (el != null) {\n      el.textContent = \"BokehJS is loading...\";\n    }\n    if (root.Bokeh !== undefined) {\n      if (el != null) {\n        el.textContent = \"BokehJS \" + root.Bokeh.version + \" successfully loaded.\";\n      }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(display_loaded, 100)\n    }\n  }\n\n\n  function run_callbacks() {\n    try {\n      root._bokeh_onload_callbacks.forEach(function(callback) {\n        if (callback != null)\n          callback();\n      });\n    } finally {\n      delete root._bokeh_onload_callbacks\n    }\n    console.debug(\"Bokeh: all callbacks have finished\");\n  }\n\n  function load_libs(css_urls, js_urls, callback) {\n    if (css_urls == null) css_urls = [];\n    if (js_urls == null) js_urls = [];\n\n    root._bokeh_onload_callbacks.push(callback);\n    if (root._bokeh_is_loading > 0) {\n      console.debug(\"Bokeh: BokehJS is being loaded, scheduling callback at\", now());\n      return null;\n    }\n    if (js_urls == null || js_urls.length === 0) {\n      run_callbacks();\n      return null;\n    }\n    console.debug(\"Bokeh: BokehJS not loaded, scheduling load and callback at\", now());\n    root._bokeh_is_loading = css_urls.length + js_urls.length;\n\n    function on_load() {\n      root._bokeh_is_loading--;\n      if (root._bokeh_is_loading === 0) {\n        console.debug(\"Bokeh: all BokehJS libraries/stylesheets loaded\");\n        run_callbacks()\n      }\n    }\n\n    function on_error(url) {\n      console.error(\"failed to load \" + url);\n    }\n\n    for (let i = 0; i < css_urls.length; i++) {\n      const url = css_urls[i];\n      const element = document.createElement(\"link\");\n      element.onload = on_load;\n      element.onerror = on_error.bind(null, url);\n      element.rel = \"stylesheet\";\n      element.type = \"text/css\";\n      element.href = url;\n      console.debug(\"Bokeh: injecting link tag for BokehJS stylesheet: \", url);\n      document.body.appendChild(element);\n    }\n\n    const hashes = {\"https://cdn.bokeh.org/bokeh/release/bokeh-2.3.3.min.js\": \"dM3QQsP+wXdHg42wTqW85BjZQdLNNIXqlPw/BgKoExPmTG7ZLML4EGqLMfqHT6ON\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.3.3.min.js\": \"8x57I4YuIfu8XyZfFo0XVr2WAT8EK4rh/uDe3wF7YuW2FNUSNEpJbsPaB1nJ2fz2\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.3.3.min.js\": \"3QTqdz9LyAm2i0sG5XTePsHec3UHWwVsrOL68SYRoAXsafvfAyqtQ+h440+qIBhS\"};\n\n    for (let i = 0; i < js_urls.length; i++) {\n      const url = js_urls[i];\n      const element = document.createElement('script');\n      element.onload = on_load;\n      element.onerror = on_error.bind(null, url);\n      element.async = false;\n      element.src = url;\n      if (url in hashes) {\n        element.crossOrigin = \"anonymous\";\n        element.integrity = \"sha384-\" + hashes[url];\n      }\n      console.debug(\"Bokeh: injecting script tag for BokehJS library: \", url);\n      document.head.appendChild(element);\n    }\n  };\n\n  function inject_raw_css(css) {\n    const element = document.createElement(\"style\");\n    element.appendChild(document.createTextNode(css));\n    document.body.appendChild(element);\n  }\n\n  \n  var js_urls = [\"https://cdn.bokeh.org/bokeh/release/bokeh-2.3.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-widgets-2.3.3.min.js\", \"https://cdn.bokeh.org/bokeh/release/bokeh-tables-2.3.3.min.js\"];\n  var css_urls = [];\n  \n\n  var inline_js = [\n    function(Bokeh) {\n      Bokeh.set_log_level(\"info\");\n    },\n    function(Bokeh) {\n    \n    \n    }\n  ];\n\n  function run_inline_js() {\n    \n    if (root.Bokeh !== undefined || force === true) {\n      \n    for (var i = 0; i < inline_js.length; i++) {\n      inline_js[i].call(root, root.Bokeh);\n    }\n    } else if (Date.now() < root._bokeh_timeout) {\n      setTimeout(run_inline_js, 100);\n    } else if (!root._bokeh_failed_load) {\n      console.log(\"Bokeh: BokehJS failed to load within specified timeout.\");\n      root._bokeh_failed_load = true;\n    } else if (force !== true) {\n      var cell = $(document.getElementById(null)).parents('.cell').data().cell;\n      cell.output_area.append_execute_result(NB_LOAD_WARNING)\n    }\n\n  }\n\n  if (root._bokeh_is_loading === 0) {\n    console.debug(\"Bokeh: BokehJS loaded, going straight to plotting\");\n    run_inline_js();\n  } else {\n    load_libs(css_urls, js_urls, function() {\n      console.debug(\"Bokeh: BokehJS plotting callback run at\", now());\n      run_inline_js();\n    });\n  }\n}(window));"
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "\n",
              "\n",
              "\n",
              "\n",
              "\n",
              "  <div class=\"bk-root\" id=\"d9efa168-4604-4e46-84f2-ce7580489468\" data-root-id=\"1002\"></div>\n"
            ]
          },
          "metadata": {
            "tags": []
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "application/javascript": [
              "(function(root) {\n",
              "  function embed_document(root) {\n",
              "    \n",
              "  var docs_json = 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\",\"dtype\":\"float32\",\"order\":\"little\",\"shape\":[2672]},\"y\":{\"__ndarray__\":\"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\",\"dtype\":\"float32\",\"order\":\"little\",\"shape\":[2672]}},\"selected\":{\"id\":\"1049\"},\"selection_policy\":{\"id\":\"1048\"}},\"id\":\"1035\",\"type\":\"ColumnDataSource\"},{\"attributes\":{\"source\":{\"id\":\"1035\"}},\"id\":\"1039\",\"type\":\"CDSView\"},{\"attributes\":{},\"id\":\"1046\",\"type\":\"BasicTickFormatter\"},{\"attributes\":{},\"id\":\"1024\",\"type\":\"SaveTool\"},{\"attributes\":{\"fill_alpha\":{\"value\":0.1},\"fill_color\":{\"field\":\"fill_color\"},\"line_alpha\":{\"value\":0.1},\"line_color\":{\"field\":\"line_color\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"1037\",\"type\":\"Scatter\"},{\"attributes\":{},\"id\":\"1045\",\"type\":\"AllLabels\"},{\"attributes\":{\"fill_color\":{\"field\":\"fill_color\"},\"line_color\":{\"field\":\"line_color\"},\"x\":{\"field\":\"x\"},\"y\":{\"field\":\"y\"}},\"id\":\"1036\",\"type\":\"Scatter\"},{\"attributes\":{},\"id\":\"1048\",\"type\":\"UnionRenderers\"}],\"root_ids\":[\"1002\"]},\"title\":\"Bokeh Application\",\"version\":\"2.3.3\"}};\n",
              "  var render_items = [{\"docid\":\"d96933c6-5b19-4192-8af8-5c0402f40ec0\",\"root_ids\":[\"1002\"],\"roots\":{\"1002\":\"d9efa168-4604-4e46-84f2-ce7580489468\"}}];\n",
              "  root.Bokeh.embed.embed_items_notebook(docs_json, render_items);\n",
              "\n",
              "  }\n",
              "  if (root.Bokeh !== undefined) {\n",
              "    embed_document(root);\n",
              "  } else {\n",
              "    var attempts = 0;\n",
              "    var timer = setInterval(function(root) {\n",
              "      if (root.Bokeh !== undefined) {\n",
              "        clearInterval(timer);\n",
              "        embed_document(root);\n",
              "      } else {\n",
              "        attempts++;\n",
              "        if (attempts > 100) {\n",
              "          clearInterval(timer);\n",
              "          console.log(\"Bokeh: ERROR: Unable to run BokehJS code because BokehJS library is missing\");\n",
              "        }\n",
              "      }\n",
              "    }, 10, root)\n",
              "  }\n",
              "})(window);"
            ],
            "application/vnd.bokehjs_exec.v0+json": ""
          },
          "metadata": {
            "tags": [],
            "application/vnd.bokehjs_exec.v0+json": {
              "id": "1002"
            }
          }
        },
        {
          "output_type": "display_data",
          "data": {
            "text/plain": [
              "<Figure size 432x288 with 0 Axes>"
            ]
          },
          "metadata": {
            "tags": []
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "nWhOsqJyP7Zn",
        "outputId": "3b49b62b-8204-40ec-8ec3-9f6a04497f58"
      },
      "source": [
        "# !pip install numpy==1.20.0"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Requirement already satisfied: numpy==1.20.0 in /usr/local/lib/python3.7/dist-packages (1.20.0)\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ogGrsptHktK_"
      },
      "source": [
        "###3.3. Sentinment Analysis with VADER"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "_QBFyaqXzmIh",
        "outputId": "0d506cc2-52ce-49ee-a89e-7b6e75a68abe"
      },
      "source": [
        "vader_model = con.sa_vader()"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "[nltk_data] Downloading package names to /root/nltk_data...\n",
            "[nltk_data]   Package names is already up-to-date!\n",
            "[nltk_data] Downloading package stopwords to /root/nltk_data...\n",
            "[nltk_data]   Package stopwords is already up-to-date!\n",
            "[nltk_data] Downloading package state_union to /root/nltk_data...\n",
            "[nltk_data]   Package state_union is already up-to-date!\n",
            "[nltk_data] Downloading package averaged_perceptron_tagger to\n",
            "[nltk_data]     /root/nltk_data...\n",
            "[nltk_data]   Package averaged_perceptron_tagger is already up-to-\n",
            "[nltk_data]       date!\n",
            "[nltk_data] Downloading package vader_lexicon to /root/nltk_data...\n",
            "[nltk_data]   Package vader_lexicon is already up-to-date!\n",
            "[nltk_data] Downloading package punkt to /root/nltk_data...\n",
            "[nltk_data]   Package punkt is already up-to-date!\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 422
        },
        "id": "tcZJDmWZkxWD",
        "outputId": "b76151e3-dc69-48a5-bc2e-602ce36b7c22"
      },
      "source": [
        "vader_model.get_text_polarity()"
      ],
      "execution_count": 23,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <td>0.0000</td>\n",
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              "    <tr>\n",
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              "      <td>0.0000</td>\n",
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              "    <tr>\n",
              "      <th>2691</th>\n",
              "      <td>0.7269</td>\n",
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            "text/plain": [
              "      Polarity\n",
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              "...        ...\n",
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              "\n",
              "[2692 rows x 1 columns]"
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          },
          "metadata": {
            "tags": []
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          "execution_count": 23
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "CvEQ75Rok2oc"
      },
      "source": [
        "###3.4. Summarization with BERT"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "ylnZBX7EznQa",
        "outputId": "f9d07ff8-921b-4fb7-dcb0-1b0c557cac6a"
      },
      "source": [
        "bert_sum_model = con.sum_bert()"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Some weights of the model checkpoint at bert-large-uncased were not used when initializing BertModel: ['cls.predictions.transform.dense.bias', 'cls.predictions.transform.LayerNorm.bias', 'cls.predictions.transform.dense.weight', 'cls.predictions.bias', 'cls.seq_relationship.bias', 'cls.seq_relationship.weight', 'cls.predictions.transform.LayerNorm.weight', 'cls.predictions.decoder.weight']\n",
            "- This IS expected if you are initializing BertModel from the checkpoint of a model trained on another task or with another architecture (e.g. initializing a BertForSequenceClassification model from a BertForPreTraining model).\n",
            "- This IS NOT expected if you are initializing BertModel from the checkpoint of a model that you expect to be exactly identical (initializing a BertForSequenceClassification model from a BertForSequenceClassification model).\n"
          ],
          "name": "stderr"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 72
        },
        "id": "iszJIOJpmriF",
        "outputId": "760964a7-11b7-498f-fbd3-befaf927f3d7"
      },
      "source": [
        "bert_sum_model.get_spec_text_sum(100,1)"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "application/vnd.google.colaboratory.intrinsic+json": {
              "type": "string"
            },
            "text/plain": [
              "\"ISLAMABAD: Pakistan's central bank has received $500 million from the International Monetary Fund (IMF) as the sixth loan tranche of an ongoing aid arrangement to support economic reforms and growth, sources told Geo News on Wednesday.\""
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 6
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "MjYbMWGlE47c"
      },
      "source": [
        "###4. Using the NLP_Controller to combine data from different models"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 733
        },
        "id": "6EAbRH4D2Jc-",
        "outputId": "eeceb647-d8f7-461d-e5d8-392f2f88bb57"
      },
      "source": [
        "con.get_full_table(bert_topic_model, vader_model)"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
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              "      <th></th>\n",
              "      <th>Article</th>\n",
              "      <th>Date</th>\n",
              "      <th>Heading</th>\n",
              "      <th>NewsType</th>\n",
              "      <th>Polarity</th>\n",
              "      <th>Topic 1</th>\n",
              "      <th>Topic 2</th>\n",
              "      <th>Topic 3</th>\n",
              "      <th>Topic 4</th>\n",
              "      <th>Topic 5</th>\n",
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              "  </thead>\n",
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              "    <tr>\n",
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              "      <td>karachi the sindh government has decided to br...</td>\n",
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              "      <td>hong kong asian markets started on an upswing ...</td>\n",
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              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>hong kong hong kong shares opened percent lowe...</td>\n",
              "      <td>2015-01-05</td>\n",
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              "      <td>2015-01-06</td>\n",
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              "    <tr>\n",
              "      <th>2687</th>\n",
              "      <td>strong dubai dubai international airport and i...</td>\n",
              "      <td>2017-03-25</td>\n",
              "      <td>Laptop ban hits Dubai for 11m weekend traveller</td>\n",
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              "      <td>-0.5574</td>\n",
              "      <td>48</td>\n",
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              "      <th>2688</th>\n",
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            "text/plain": [
              "                                                Article  ... Topic 5\n",
              "0     karachi the sindh government has decided to br...  ...      12\n",
              "1     hong kong asian markets started on an upswing ...  ...      19\n",
              "2     hong kong hong kong shares opened percent lowe...  ...      35\n",
              "3     hong kong asian markets tumbled tuesday follow...  ...      59\n",
              "4     new york us oil prices monday slipped below a ...  ...       9\n",
              "...                                                 ...  ...     ...\n",
              "2687  strong dubai dubai international airport and i...  ...      30\n",
              "2688  strong beijing former prime minister shaukat a...  ...      20\n",
              "2689  strong washington uber has grounded its fleet ...  ...       3\n",
              "2690  strong beijing the new development bank plans ...  ...      12\n",
              "2691  strong karachi karachi based technology incuba...  ...      20\n",
              "\n",
              "[2692 rows x 10 columns]"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 5
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 376
        },
        "id": "C59tvHhqFPSn",
        "outputId": "4ea7ab5d-80dd-44c6-a8db-f882be84f154"
      },
      "source": [
        "con.get_topic_polarity_plots(2, bert_topic_model, vader_model)"
      ],
      "execution_count": 5,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "image/png": 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\n",
            "text/plain": [
              "<Figure size 1800x720 with 1 Axes>"
            ]
          },
          "metadata": {
            "tags": [],
            "needs_background": "light"
          }
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "EilhDoIUFkpM"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}