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

The expansion of the web and emergence of a large number of social networking sites
(SNS) have empowered users to easily interconnect on a shared platform. A social network …

We propose a temporal latent space model for link prediction in dynamic social networks,
where the goal is to predict links over time based on a sequence of previous graph …

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 …

This paper presents a survey of previous studies done on the problem of tracking community
evolution over time in dynamic social networks. This problem is of crucial importance in the …

Community detection aims at discovering the structure, behavior, dynamics, and
organization of a complex network by finding cohesive groups where nodes (entities) are, in …

Recently, there has been significant interest in the study of the community search problem in
social and information networks: given one or more query nodes, find densely connected …

Detecting communities in dynamic evolving networks is of great interest. It has received
tremendous attention from researchers. One promising solution is to update communities …

Communities can intuitively be defined as subsets of nodes of a graph with a dense
structure in the corresponding subgraph. However, for mining such communities usually …

Community detection is an important research area in social networks analysis where we
are concerned with discovering the structure of the social network. Detecting communities is …