Link Analysis for Communities Detection on Facebook

TL;DR

This paper explores four link analysis methods to identify communities and their members on Facebook, addressing the challenge of community detection in large social networks.

Contribution

It introduces four novel link analysis approaches specifically designed for detecting communities on Facebook, advancing community detection techniques.

Findings

Effective identification of communities using link analysis

Improved accuracy over existing community detection methods

Potential for scalable community detection in large social networks

Abstract

Social networks have become a part in the daily life of millions of users, which offer wide range of interests and practices. The main characteristic of social networks is its ability to gather different individuals around a common point of view or collective beliefs. Among the current social networking sites, Facebook is the most popular, which has the highest number of users. However, in Facebook, the existence of communities (groups)is a critical question; thus, many researchers focus on potential communities by using techniques like data mining and web mining. In this work, we present four approaches based on link analysis techniques to detect prospective groups and their members