Triangle-oriented Community Detection considering Node Features and Network Topology

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 trianglebased 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 nonoverlapping 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.

Assessing Spillover Effects of Medications for Opioid Use Disorder on HIV Risk Behaviors among a Network of People Who Inject Drugs

“…An area for future research could compare the performance of community detection against other methods such as nearest neighbors and chain graphs in networks with varying characteristics (e.g., significance of community structure, community sizes, and number of communities). Future research may also consider community detection methods that also account for the characteristics of both nodes and edges [63][64][65]. A best-case scenario favoring an alternative hypothesis of the protective effect of MOUD treatment against HIV risk behaviors among these 56 participants would imply that untreated participants do experience the outcome, and the treated participants do not experience the outcome.…”