04450nam 22007335 450 991029899350332120200629210025.03-319-12188-X10.1007/978-3-319-12188-8(CKB)3710000000337860(EBL)1968292(OCoLC)908089313(SSID)ssj0001424600(PQKBManifestationID)11748711(PQKBTitleCode)TC0001424600(PQKBWorkID)11368479(PQKB)10811185(MiAaPQ)EBC1968292(DE-He213)978-3-319-12188-8(PPN)183521498(EXLCZ)99371000000033786020150113d2014 u| 0engur|n|---|||||txtccrSocial Network Analysis - Community Detection and Evolution[electronic resource] /edited by Rokia Missaoui, Idrissa Sarr1st ed. 2014.Cham :Springer International Publishing :Imprint: Springer,2014.1 online resource (282 p.)Lecture Notes in Social Networks,2190-5428Description based upon print version of record.3-319-12187-1 Includes bibliographical references and index.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.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.Lecture Notes in Social Networks,2190-5428Data miningSocial sciencesMathematicsPhysicsData Mining and Knowledge Discoveryhttps://scigraph.springernature.com/ontologies/product-market-codes/I18030Methodology of the Social Scienceshttps://scigraph.springernature.com/ontologies/product-market-codes/X17000Mathematics in the Humanities and Social Scienceshttps://scigraph.springernature.com/ontologies/product-market-codes/M32000Applications of Graph Theory and Complex Networkshttps://scigraph.springernature.com/ontologies/product-market-codes/P33010Data mining.Social sciences.Mathematics.Physics.Data Mining and Knowledge Discovery.Methodology of the Social Sciences.Mathematics in the Humanities and Social Sciences.Applications of Graph Theory and Complex Networks.004006.312300.1519Missaoui Rokiaedthttp://id.loc.gov/vocabulary/relators/edtSarr Idrissaedthttp://id.loc.gov/vocabulary/relators/edtBOOK9910298993503321Social Network Analysis - Community Detection and Evolution1992600UNINA