Community detection is a common problem in graph data analytics that consists of finding
groups of densely connected nodes with few connections to nodes outside of the group. In …

A network is a typical expressive form of representing complex systems in terms of vertices
and links, in which the pattern of interactions amongst components of the network is intricate …

Algorithms to find communities in networks rely just on structural information and search for
cohesive subsets of nodes. On the other hand, most scholars implicitly or explicitly assume …

Twitter is one of the most popular microblogging services, which is generally used to share
news and updates through short messages restricted to 280 characters. However, its open …

Purpose The spread of rumors on social media has caused increasing concerns about an
under-informed or even misinformed public when it comes to scientific issues. However …

The amount of graph-structured data has recently experienced an enormous growth in many
applications. To transform such data into useful information, fast analytics algorithms and …

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

The enormous growth of the Web led to the birth of different network structures. Therefore,
one of the important issues in the field of complex network analysis is to find and exploit the …

One of the most interesting topics in the scope of social network analysis is dynamic
community detection, keeping track of communities' evolutions in a dynamic network. This …

Network science is the field dedicated to the investigation and analysis of complex systems
via their representations as networks. We normally model such networks as graphs: sets of …