eigenvector-centrality

Social Network Analysis and Visualization software application.

Graphs and passing networks in football.

NetworkX clone in JavaScript

Demo on applying the concept of network analysis on a network of connected railway stations, attempting to identify the important stations (nodes) in this network. Web scraping techniques using rvest package is also briefly discussed upon.

Analysis of London street gang network

This project evolves around the concept of networks, centralities, and community detection, and infection simulation.

Gene expression analysis approaches using knowledge graph of Protein-Protein Interaction from STRING database

This project utilizes various metrics to analyze a graph network based on data of ENZYMES_g295

A PHP library to do calculates Eigenvector Centrality of a undirected graph. Eigenvector Centrality is one of the Social Network Analysis algorithms.

Unsupervised learning of Eigenvector centrality with GNN

Mencari influencer user di Twitter menggunakan metode Centrality EigenVector dengan topik game Heaven Burns Red

MATLAB experimental code verifying the limiting behavior of parameter-dependent network centrality measures (ESC, ETC, RC, Katz) on directed and undirected graphs, based on Benzi & Klymko (2015).

Social-network influencer analysis using eigenvector centrality, graph visualization, Next.js, and FastAPI.

This repository is devoted to the field of Graph Analysis and related topics.

Network Analysis: A comparative Analysis of Centrality Measures for the Brain Subregions of two Populations of Prairie Voles

Eigenvector Centrality For Temporal and Multiplex Networks (C++ and Python wrapper)

Numerical Linear Algebra project, Skoltech, Term 2, 2019

Analyzes the top 10 most "important" characters in the Harry Potter universe using centrality metrics (degree centrality, eigenvector centrality, closeness centrality)

This project applies Social Network Analysis (SNA) to EHR data from 2,000 patients to reveal links among conditions, drugs, and risk factors. Three networks were built to identify key diseases, comorbidity clusters, and treatment hubs, supporting data-driven insights for personalized healthcare.