• This tool uses advanced machine learning and natural language processing techniques to provide valuable insights into the content and privacy practices of news sites.

Main Features

• Extracting information from web pages
• Content sentiment analysis
• Detection of known tracking scripts
• Identification of potentially suspicious external links
• IP Tracking Prediction Using Machine Learning

Requirements

• Python 3.7 or higher

Installation

Clone this repository:

    git clone https://github.com/mrfelpa/LinkAnalyzer.git
    

    cd linkanalyzer

• Install dependencies:

    pip install -r requirements.txt
  

Use

• To analyze a news link, run the following command:

    python linkanalyzer.py --url https://example.com/news
  

  • You can also run the script without arguments, and it will request the URL interactively:

    python linkanalyzer.py
    

Machine Learning Model

• The script uses a Naive Bayes Multinomial classifier trained with an example dataset, this model is used to predict whether a page might be tracking the user's IP based on the extracted text.

• You can tune the machine learning model by modifying the training data in the train_model functio, add more examples to improve prediction accuracy.

Contributions

• We value contributions from the community, if you have any questions or suggestions, please open an issue