Overview
- Describes novel results in community detection and/or evolution
- Clearly written and generously illustrated
- Covers hot topics in social network such as community evolution, information propagation and influence maximization
- Includes supplementary material: sn.pub/extras
Part of the book series: Lecture Notes in Social Networks (LNSN)
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About this book
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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Keywords
Table of contents (11 chapters)
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Front Matter
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Back Matter
Reviews
“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)
Editors and Affiliations
Bibliographic Information
Book Title: Social Network Analysis - Community Detection and Evolution
Editors: Rokia Missaoui, Idrissa Sarr
Series Title: Lecture Notes in Social Networks
DOI: https://doi.org/10.1007/978-3-319-12188-8
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer International Publishing Switzerland 2014
Hardcover ISBN: 978-3-319-12187-1Published: 26 January 2015
Softcover ISBN: 978-3-319-38474-0Published: 06 October 2016
eBook ISBN: 978-3-319-12188-8Published: 13 January 2015
Series ISSN: 2190-5428
Series E-ISSN: 2190-5436
Edition Number: 1
Number of Pages: XVIII, 272
Number of Illustrations: 6 b/w illustrations, 102 illustrations in colour
Topics: Data Mining and Knowledge Discovery, Methodology of the Social Sciences, Mathematics in the Humanities and Social Sciences, Applications of Graph Theory and Complex Networks