SLPA: Uncovering Overlapping Communities in Social Networks via A Speaker-listener Interaction Dynamic Process

TL;DR

This paper introduces SLPA, a novel label propagation algorithm that effectively detects overlapping communities in social networks by modeling dynamic speaker-listener interactions, improving the analysis of complex social structures.

Contribution

The paper presents a new framework and algorithm for uncovering overlapping communities and nodes in social networks using dynamic label exchange processes.

Findings

SLPA accurately identifies overlapping communities with high diversity.

The method outperforms existing algorithms in detecting overlapping structures.

SLPA is versatile for analyzing various social network configurations.

Abstract

Overlap is one of the characteristics of social networks, in which a person may belong to more than one social group. For this reason, discovering overlapping structures is necessary for realistic social analysis. In this paper, we present a novel, general framework to detect and analyze both individual overlapping nodes and entire communities. In this framework, nodes exchange labels according to dynamic interaction rules. A specific implementation called Speaker-listener Label Propagation Algorithm (SLPA1) demonstrates an excellent performance in identifying both overlapping nodes and overlapping communities with different degrees of diversity.