Local Core Members Aided Community Structure Detection

TL;DR

This paper introduces a novel community detection method in social networks that leverages the closeness of relations among neighbors, using gravity calculations to efficiently identify community structures with low computational complexity.

Contribution

It proposes a new approach based on local core members and relation gravity for community detection, improving efficiency and accuracy over existing methods.

Findings

Effective detection of community structures in social networks.

Low computational complexity demonstrated through experiments.

Outperforms some existing community detection algorithms.

Abstract

The relationship of friends in social networks can be strong or weak. Some research works have shown that a close relationship between friends conducts good community structure. Based on this result, we propose an effective method in detecting community structure in social networks based on the closeness of relations among neighbors. This method calculates the gravity between each neighbor node to core nodes, then makes judgement if the node should be classified in the community or not, and finally form the process of community detection. The experimental results show that the proposed method can mine the social structure efficiently with a low computational complexity