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This Python script fetches coauthor information from the provided DBLP URLs of professors and generates a network graph visualizing these relationships. The script processes up to 1-depth of coauthors: primary coauthors directly connected to the major professors

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Academic Network Visualization Script

This script allows you to input the URLs of professors from DBLP (https://dblp.org/) and generates a network graph with their 1-depth coauthors from 2020s to current record. The resulting graph visualizes the collaborative relationships between these professors and their coauthors.

Setup

Prerequisites

Ensure you have the following installed:

  • Python 3.x
  • The required Python packages

Installation

  1. Clone the repository or download the script.
  2. Navigate to the directory containing the script.
  3. Install the required packages using pip:
pip install requests beautifulsoup4 networkx matplotlib

Usage

  1. Edit the script to include the desired professor URLs:

    Update the professor_urls dictionary in the script to include the URLs of the professors you want to analyze. For example:

    professor_urls = {
          "[ProfessorName]": "[dplp_url]",
    }
  2. Run the script:

    Execute the script in your terminal:

    python academic_network.py
  3. View the output:

    The script will generate a network graph and save it as full_network.png in the current directory.

License

This project is licensed under the MIT License.

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This Python script fetches coauthor information from the provided DBLP URLs of professors and generates a network graph visualizing these relationships. The script processes up to 1-depth of coauthors: primary coauthors directly connected to the major professors

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