… The aim of this paper is clustering social networks with a better community structure and …
In this paper an algorithm is proposed for clustering in social networks. Random walks are used …

… In this case, cluster analysis is one of the main methods of typology which demands …
completion of the clustering algorithm depend on each other. We show that cluster analysis of data …

… clustering analysis of social network is studied. In the second section, a social network clustering
… The biggest challenge of social network clustering analysis is how to divide objects into …

… Abstract—Motivated by applications in social network community analysis, we introduce a
new clustering paradigm termed motif clustering. Unlike classical clustering, motif clustering …

… clustering, by accounting for both team structural and attribute similarity from the perspective
of social network analysis. … by combining tie strength and social cohesion among teams via …

… In addition, these methods proved to be quite effective in solving cluster analysis
problems, thus becoming attractive for graph partitioning and community detection purposes. …

… Then, a K-means clustering approach is implemented to have groups of related studies for …
descriptive analysis is part to demonstrate a general view, bibliometric analysis and clustering …

… ’s societal network and used it for redefining the social network … Further, we had defined the
Social network in terms of graph … Fiksel’s societal network and social network with respect to …

… Here we propose to exploit the social relationships for recommendation: users are clustered
based on the social network built from various relationships. When we have user clusters, …

… The objective of this investigation was to examine STI transmission within different groups,
using both social network analysis and cluster analysis. Routine partner notification data were …