YouTube NLP Comment Analysis

This repository contains the code and resources for analyzing YouTube comments using Natural Language Processing (NLP) techniques.

Introduction

YouTube NLP Comment Analysis is a project that aims to extract sentiment and gain valuable insights into the overall perception and sentiment of viewers towards specific videos. By utilizing NLP techniques, we can analyze user-generated comments on YouTube and understand the sentiment expressed by viewers.

Schema

Features

• Collect YouTube comments using the web scraping techniques.
• Preprocess comments by removing noise, such as special characters, URLs, and excessive punctuation.
• Perform sentiment analysis using lexicon-based methods or machine learning algorithms.
• Visualize sentiment patterns using bar charts

Installation

1. Clone the repository:

   git clone https://github.com/jpkrajewski/youtube-nlp-comment-analysis.git

2. Run Docker-Compose

   cd youtube-nlp-comment-analysis; docker compose up --build

3. Go to localhost:8000

Results

The project generates visualizations and reports that provide insights into the sentiment patterns of YouTube comments. These include:

Bar charts showing sentiment distribution, categorizing comments as negative, neutral, or positive.