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