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

Community structure is one of the most relevant features encountered in numerous real-
world applications of networked systems. Despite the tremendous effort of a large …

Community detection is one of the most popular researches in a variety of complex systems,
ranging from biology to sociology. In recent years, there's an increasing focus on the rapid …

A network is a collection of nodes and edges, where an edge connects two nodes. Many
social, natural and engineered systems can be represented as networks. Examples include …

We investigate the effects of modular and temporal connectivity patterns on epidemic
spreading. To this end, we introduce and analytically characterise a model of time-varying …

In the study of networks, it is often insightful to use algorithms to determine mesoscale
features such as 'community structure', in which densely connected sets of nodes constitute …

Modularity is widely used to effectively measure the strength of the community structure
found by community detection algorithms. However, modularity maximization suffers from …

We present a new method, State-based Dynamic Community Structure, that detects time-
dependent community structure in networks of brain regions. Most analyses of functional …

Detecting and analyzing community structure is a challenging topic in dynamic social
network analysis. Although the number of methods in this area is on the rise, there are only a …

In recent years, multi-view graph partitioning has attracted more and more attention, but
most efforts have been made to develop graph partitioning approaches directly in the …