Triangle-oriented Community Detection considering Node Features and Network Topology

TL;DR

This paper introduces a triangle-oriented community detection method that considers higher-order network structures, node features, and topology to improve community quality and address issues like unbalanced communities and free-rider effects.

Contribution

It proposes a novel triangle-based quality metric and a two-level constraint framework for more accurate community detection in attributed networks.

Findings

Effective in detecting both overlapping and non-overlapping communities.

Reduces unbalanced community sizes and free-rider effects.

Demonstrates superior performance over existing methods.

Abstract

The joint use of node features and network topology to detect communities is called community detection in attributed networks. Most of the existing work along this line has been carried out through objective function optimization and has proposed numerous approaches. However, they tend to focus only on lower-order details, i.e., capture node features and network topology from node and edge views, and purely seek a higher degree of optimization to guarantee the quality of the found communities, which exacerbates unbalanced communities and free-rider effect. To further clarify and reveal the intrinsic nature of networks, we conduct triangle-oriented community detection considering node features and network topology. Specifically, we first introduce a triangle-based quality metric to preserve higher-order details of node features and network topology, and then formulate so-called two-level constraints to encode lower-order details of node features and network topology. Finally, we develop a local search framework based on optimizing our objective function consisting of the proposed quality metric and two-level constraints to achieve both non-overlapping and overlapping community detection in attributed networks. Extensive experiments demonstrate the effectiveness and efficiency of our framework and its potential in alleviating unbalanced communities and free-rider effect.