A New Comparative Definition of Community and Corresponding Identifying Algorithm

TL;DR

This paper introduces a novel community definition based on internal and external node degrees and presents an algorithm that detects communities using an attractive force model, effectively analyzing various networks.

Contribution

It proposes a new community definition and an algorithm that detects communities without extra parameters, improving network division analysis.

Findings

Effective detection of communities in artificial and real-world networks

Provides clear network division and group formation insights

Works well on Zachary Karate club and College football networks

Abstract

In this paper, a new comparative definition for community in networks is proposed and the corresponding detecting algorithm is given. A community is defined as a set of nodes, which satisfy that each node's degree inside the community should not be smaller than the node's degree toward any other community. In the algorithm, the attractive force of a community to a node is defined as the connections between them. Then employing attractive force based self-organizing process, without any extra parameter, the best communities can be detected. Several artificial and real-world networks, including Zachary Karate club network and College football network are analyzed. The algorithm works well in detecting communities and it also gives a nice description for network division and group formation.