Social Network Analysis - Community Detection and Evolution

• Corporate Author: SpringerLink (Online service)
• Other Authors: Missaoui, Rokia (Editor), Sarr, Idrissa (Editor)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2014.
• Series: Lecture Notes in Social Networks,
• Subjects: Computer science.; Data mining.; Mathematics.; Social sciences.; Physics.; Computer Science.; Data Mining and Knowledge Discovery.; Methodology of the Social Sciences.; Mathematics in the Humanities and Social Sciences.; Complex Networks.

 This book is devoted to recent progress in social network analysis with a high focus on community detection and evolution. The eleven chapters cover the identification of cohesive groups, core components and key players either in static or dynamic networks of different kinds and levels of heterogeneity. Other important topics in social network analysis such as influential detection and maximization, information propagation, user behavior analysis, as well as network modeling and visualization are also presented. Many studies are validated through real social networks such as Twitter. This edited work will appeal to researchers, practitioners and students interested in the latest developments of social network analysis. 

 The Emergence of Communities and their Leaders on Twitter Following an Extreme Event -- Hierarchical and Matrix Structures in a Large Organizational Email Network: Visualization and Modeling Approaches -- Networks of Different Perspectives for Inter-network Community Evolution -- Study of Influential Trends, Communities, and Websites on the Post-Election Events of Iranian Presidential Election in Twitter -- Entanglement in Multiplex Networks: Understanding Group Cohesion in Homophily Networks -- An Elite Grouping of Individuals for Expressing a Core Identity Based on the Temporal Dynamicity or the Semantic -- The Power of Consensus: Random Graphs Still Have No Communities -- Link Prediction in Heterogeneous Collaboration -- Characterization of User Online Dating Behavior and Preference on a Large Online Dating -- Latent Tunnel Based Information Propagation in Microblog Networks -- Maximization with Network Abstractions.