Multi-View Community Detection in Facebook Public Pages

TL;DR

This paper introduces a multi-view clustering approach to detect communities in Facebook public pages, effectively integrating diverse user activities to improve community detection accuracy across multiple pages.

Contribution

It presents a novel multi-view clustering method tailored for Facebook public pages, addressing diversity in user activities and community structures across pages.

Findings

Reduces isolated nodes in community detection

Improves community structure quality

Effective across multiple Facebook pages

Abstract

Community detection in social networks is widely studied because of its importance in uncovering how people connect and interact. However, little attention has been given to community structure in Facebook public pages. In this study, we investigate the community detection problem in Facebook newsgroup pages. In particular, to deal with the diversity of user activities, we apply multi-view clustering to integrate different views, for example, likes on posts and likes on comments. In this study, we explore the community structure in not only a given single page but across multiple pages. The results show that our method can effectively reduce isolates and improve the quality of community structure.