LinkingMap is a Python project that analyzes a webpage, extracts all links, counts the number of links by domain, and creates a visual representation of the link distribution by domain. The central node represents the scanned domain, and it is connected with lines to other domains. Self-links are colored green and labeled with "(self)".

This project uses the following Python libraries:

• requests: To fetch the webpage content.
• BeautifulSoup from bs4: To parse the HTML and extract links.
• collections.Counter: To count links by domain.
• urllib.parse: To handle and parse URLs.
• matplotlib: To create a visual representation.
• networkx: To create and manage the network graph.

Ensure you have Python 3 and pip installed. You also need virtualenv to create an isolated environment for the project.

1. Clone the repository:

git clone https://github.com/Liam-Nothing/LinkingMap-SEO
cd LinkingMap-SEO

2. Create and activate a virtual environment:

python3 -m venv venv
source venv/bin/activate

3. Install the required libraries:

pip install -r requirements.txt

1. Ensure your virtual environment is activated:

source venv/bin/activate

2. Run the script with a valid URL:

python link_extractor.py https://example.com

Replace https://example.com with the URL you want to analyze. The script will fetch the webpage, extract links, count domains, and generate a bar chart saved as domain_distribution.png.