Social Network Analysis - Community Detection and Evolution (eBook, PDF)

Redaktion: Missaoui, Rokia; Sarr, Idrissa

• Format: PDF

Produktbeschreibung

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.

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Produktdetails

• Verlag: Springer International Publishing
• Seitenzahl: 272
• Erscheinungstermin: 13. Januar 2015
• Englisch
• ISBN-13: 9783319121888
• Artikelnr.: 43789820

Inhaltsangabe

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.

Rezensionen

"This volume presents interesting approaches in relation to communities interacting via social networks ... . The volume may be of interest to specialists mining social network data and to some advanced students wishing to further their research. Each chapter has its own references, and the collective work has a common glossary and index." (L.-F. Pau, Computing Reviews, March, 2016)