An Introduction to Community Detection in Multi-layered Social Network

TL;DR

This paper introduces a novel method for detecting communities in multi-layered social networks by utilizing a multi-layered edge clustering coefficient, addressing the complexity of modern social data.

Contribution

It proposes a new approach specifically designed for multi-layered social networks, which had not been adequately addressed in prior research.

Findings

Effective community detection in multi-layered networks

Utilizes multi-layered edge clustering coefficient

Addresses complexity of modern social data

Abstract

Social communities extraction and their dynamics are one of the most important problems in today's social network analysis. During last few years, many researchers have proposed their own methods for group discovery in social networks. However, almost none of them have noticed that modern social networks are much more complex than few years ago. Due to vast amount of different data about various user activities available in IT systems, it is possible to distinguish the new class of social networks called multi-layered social network. For that reason, the new approach to community detection in the multi-layered social network, which utilizes multi-layered edge clustering coefficient is proposed in the paper.