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A fast clustering algorithm for mining social network data

2014/03/05 by Saeede Ajorlou, Ajorlou, Saeede, Issac Shams +3
Computer Science · Physics and Astronomy · #62H30 #91C20 #Advanced Clustering Algorithms Research #Complex Network Analysis Techniques #FOS: Computer and information sciences #FOS: Physical sciences #H.2.8 #I.2.1 #Network Security and Intrusion Detection #Physics and Society (physics.soc-ph) #Social and Information Networks (cs.SI) #acm:62H30 #acm:91C20 #cs.SI #msc:62H30 #msc:91C20 #physics.soc-ph

paper · pdf · doi:10.48550/arxiv.1403.1214

This paper has been withdrawn by the author due to a crucial sign error in figures

openalex publication_date 2014/03/05 · arxiv created 2014/08/29 · arxiv updated 2014/09/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

Many groups with diverse convictions are interacting online. Interactions in online communities help people to engage each other and enhance understanding across groups. Online communities include multiple sub-communities whose members are similar due to social ties, characteristics, or ideas on a topic. In this research, we are interested in understanding the changes in the relative size and activity of these sub-communities, their merging or splitting patterns, and the changes in the perspectives of the members of these sub-communities due to endogenous dynamics inside the community.

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