This paper aims to provide a comprehensive critical overview on how entities and their
interactions in Complex Networked Systems (CNS) are modelled across disciplines as they …

In social network analysis, community detection is a basic step to understand the structure,
function and semantics of networks. Some conventional community detection methods may …

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

While the majority of methods for community detection produce disjoint communities of
nodes, most real-world networks naturally involve overlapping communities. In this paper, a …

Community detection in complex network has become a vital step to understand the
structure and dynamics of networks in various fields. However, traditional node clustering …

Change point detection in social networks is an important element in developing the
understanding of dynamic systems. This complex and growing area of research has no clear …

With the emergence of Online Social Networks (OSNs) as an effective medium of information
dissemination, its abuse in spreading misinformation has become a great concern to its …

Community detection is an important tool to analyze hidden information such as functional
module and topology structure in complex networks. Compared with traditional community …

Community detection is a challenging issue because most existing methods are not well
suited for complex social networks with ambiguous structures. In this paper, we propose a …

This study considers the problem of hybrid community detection in attributed networks based
on the information of network topology and attributes with the aim to address the following …