Hidden Community Detection in Social Networks

TL;DR

This paper presents HICODE, a novel method for detecting hidden and dominant community structures in social networks by weakening dominant communities to reveal underlying hidden ones, outperforming existing methods.

Contribution

HICODE introduces a new approach that simultaneously uncovers hidden and dominant communities by adjusting their strengths, addressing a key challenge in network analysis.

Findings

HICODE outperforms state-of-the-art methods in real-world networks.

It uncovers multiple non-redundant communities linked to social attributes.

The method reveals latent communities without known ground truth.

Abstract

We introduce a new paradigm that is important for community detection in the realm of network analysis. Networks contain a set of strong, dominant communities, which interfere with the detection of weak, natural community structure. When most of the members of the weak communities also belong to stronger communities, they are extremely hard to be uncovered. We call the weak communities the hidden community structure. We present a novel approach called HICODE (HIdden COmmunity DEtection) that identifies the hidden community structure as well as the dominant community structure. By weakening the strength of the dominant structure, one can uncover the hidden structure beneath. Likewise, by reducing the strength of the hidden structure, one can more accurately identify the dominant structure. In this way, HICODE tackles both tasks simultaneously. Extensive experiments on real-world networks demonstrate that HICODE outperforms several state-of-the-art community detection methods in uncovering both the dominant and the hidden structure. In the Facebook university social networks, we find multiple non-redundant sets of communities that are strongly associated with residential hall, year of registration or career position of the faculties or students, while the state-of-the-art algorithms mainly locate the dominant ground truth category. In the Due to the difficulty of labeling all ground truth communities in real-world datasets, HICODE provides a promising approach to pinpoint the existing latent communities and uncover communities for which there is no ground truth. Finding this unknown structure is an extremely important community detection problem.