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Extensive Benchmarking of community detection algorithms

Description

This project contains analysis and results from artificial and social benchmark analysis.

Benchmark Workflow

Benchmark Workflow

Folder Structure

  • Figures/: Contains the figures used in the project.
  • LFR_Results/: Contains results from artificial benchmark analysis.
  • Social_benchmark_results/: Contains results from social benchmark analysis.
  • Social_networks/: Contains datasets used for benchmarking.
  • LFR_networks/: Folders containing LFR networks used for benchmarking.
  • community_detection/: Contains the Python module developed for implementing community detection algorithms. This directory also includes a README file with detailed information about the package.

Usage

To reobtain the figures, run the following Jupyter notebooks:

  • LFR_Results.ipynb
  • Social_Results.ipynb
  • Estimating_mu.ipynb

Installation

To install the Python module for community detection, navigate to the community_detection directory and run:

pip install .