Identifying meaningful community structure in social networks is a hard problem, and
extreme network size or sparseness of the network compound the difficulty of the task. With a …

Revealing the latent community structure, which is crucial to understanding the features of
networks, is an important problem in network and graph analysis. During the last decade …

Analysis of networks and in particular discovering communities within networks has been a
focus of recent work in several fields and has diverse applications. Most community …

While many recently proposed methods aim to detect network communities in large
datasets, such as those generated by social media and telecommunications services, most …

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 …

Community detection is an important task in social network analysis, allowing us to identify
and understand the communities within the social structures provided by the network …

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 …

A vital problem tackled in the network analysis literature is community structure identification
in social networks. There are many solutions to the community detection problem …

Network vertices are often divided into groups or communities with dense connections within
communities and sparse connections between communities. Community detection has …

Abstract Social Network Analysis (SNA) has gained popularity as a way to unveil and
identify useful social patterns as communities among users. However the continuous …