… community detection methods for node-attributed social networks. What is more, we propose
a classification of them based on when and how they use and fuse network … social network …

… community structure of the compressed social network, we propagate the community result to
the rest of the social network… algorithm produces high quality communities comparable to or …

… of social network analysis related to community detection and uses … social media data. It
is a self-contained book and covers important topics regarding community detection in social …

… Hybrid Recommendation Through Community Detection (HRTCD) for friend prediction with
linear runtime complexity that makes full use of the characteristics of social media based on …

… In the last decade, social network analysis techniques and community detection algorithms
… While community detection algorithms have been widely used for social network analysis, a …

… This study designs a decision support method that consists of a constrained community
detection (CCD) method and a multistage multicost consensus (MSMulCC) model. The CCD …

… The complexity of the approach is crucial in social network community detection due to their
… The processing time of a GHSOM is proportional to the social network size n. Therefore, the …

… community detection. Specifically, we provide a comprehensive review of the existing community
detection … attributes of social network, eg, user interests, to discover community. Yin et al…

… In this paper, an evaluation of eight community detection algorithms available in the “igraph”
package is performed. The library is an open-source collection of graph manipulation and …

… communities exist in network systems, such as the protein-protein intersection networks [2],
[3], WWW (World Wide Web) [4], and food web [5], [6]. Community detection … , “social network …