Several research studies have shown that complex networks modeling real-world
phenomena are characterized by striking properties:(i) they are organized according to …

Dynamic networks are used in a wide range of fields, including social network analysis,
recommender systems and epidemiology. Representing complex networks as structures …

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 …

With the rapid expansion of the scale of a dynamic network, local community evolution
analysis attracts much attention because of its efficiency and accuracy. It concentrates on a …

Community discovery is one of the most challenging tasks in social network analysis. During
the last decades, several algorithms have been proposed with the aim of identifying …

Discovering and tracking communities in time-varying networks is an important task in
network science, motivated by applications in fields ranging from neuroscience to sociology …

In the mobile Internet of Things (IoT), dynamic community discovery has attracted increasing
attention, because it can provide strong reliability and security for mobile IoT applications …

Description of temporal networks and detection of dynamic communities have been hot
topics of research for the last decade. However, no consensual answers to these challenges …

Abstract Description of temporal networks and detection of dynamic communities have been
hot topics of research for the last decade. However, no consensual answers to these …

Recent developments in the internet and technology have made major advancements in
tools that facilitate the collection of social data, opening up thus new opportunities for …