Sensibly highlighting the hidden structures of many real-world networks has attracted
growing interest and triggered a vast array of techniques on what is called nowadays …

Evolutionary algorithms have been demonstrated to be very competitive in the community
detection for complex networks. They, however, show poor scalability to large-scale …

Over the past couple of decades, the research area of network community detection has
seen substantial growth in popularity, leading to a wide range of researches in the literature …

Community detection in social network analysis is usually considered as a single objective
optimization problem, in which different heuristics or approximate algorithms are employed …

Abstract In modern Online Social Networks (OSNs), the need to detect users' communities
based on their interests and social connections has became a more and more important …

Detecting communities in real and complex networks is a highly contested topic in network
analysis. Although many metaheuristic-based algorithms for community detection have been …

In this paper, a discrete moth–flame optimization algorithm for community detection (DMFO-
CD) is proposed. The representation of solution vectors, initialization, and movement …

Designing multiobjective evolutionary algorithms (MOEAs) for community detection in
complex networks has attracted much attention of researchers recently. However, most of …

There is a surge of community detection study on complex network analysis in recent years,
since communities often play important roles in network systems. However, many real …

In order to analyze complex networks to find significant communities, several methods have
been proposed in the literature. Modularity optimization is an interesting and valuable …