Library of graph clustering algorithms

A detailed analysis of an email network between 143 employees of Enron company

Predicting new link, detecting communities on Amazon Product Co-Purchasing Network. Recommending books based on the underlying network related information. Demo Video Link -

Implementation of Girvan-Newman Algorithm using Brandes Algorithm for Community/cluster finding

EECE 5645 Project: Performing community detection on Reddit Hyperlink network dataset and leverage the power of Spark and GraphFrames

This project implements a community detection algorithm using divisive hierarchical clustering (Girvan-Newman algorithm).

We have compared the different community detection algorithms for multiple real-world social networks with some standard datasets.

Python implementations of Community Detection Algorithms, including Cliques, k-cores, SNN, IHCS, LCMA, Girvan-Newman.

Notebook of the course "Algorithms and Complexity"

Deteksi Komunitas menggunakan Algoritma Girvan-Newman

A team project for the course Algorithm Analysis and Design at IIIT-Hyderabad. Primarily features modelling the stock market as a graph, testing the metrics of numerous algorithms for modeling correlation networks and detecting market fragmentation.

This project implements an edge-removal community detection algorithm based on edge betweenness centrality (inspired by the Girvan-Newman Algorithm) on a subsampled Flickr graph using igraph, iteratively removing high-betweenness edges to detect and visualize social communities.

This project implements the Girvan-Newman and Louvain algorithms from scratch for community detection in graphs, using datasets like Wiki-Vote and LastFM-Social. It includes automated stopping criteria, dendrogram visualization, and performance comparisons.