Overview
- Presents overviews of problems and recommended solutions in social network analysis such as link prediction, influence maximization, and block modelling in complex networks
- Explores new areas such as sarcasm and sentiment analysis, block modelling in dynamic networks using stochastic approaches, and behavior modelling of social network users
- Features novel research topics such as social network user delurking, and threat assessment in social engineering
- Includes supplementary material: sn.pub/extras
Part of the book series: Lecture Notes in Social Networks (LNSN)
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Table of contents (10 chapters)
Keywords
About this book
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Editors and Affiliations
Bibliographic Information
Book Title: Trends in Social Network Analysis
Book Subtitle: Information Propagation, User Behavior Modeling, Forecasting, and Vulnerability Assessment
Editors: Rokia Missaoui, Talel Abdessalem, Matthieu Latapy
Series Title: Lecture Notes in Social Networks
DOI: https://doi.org/10.1007/978-3-319-53420-6
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer International Publishing AG 2017
Hardcover ISBN: 978-3-319-53419-0Published: 30 April 2017
Softcover ISBN: 978-3-319-85149-5Published: 25 July 2018
eBook ISBN: 978-3-319-53420-6Published: 29 April 2017
Series ISSN: 2190-5428
Series E-ISSN: 2190-5436
Edition Number: 1
Number of Pages: XIII, 255
Number of Illustrations: 22 b/w illustrations, 68 illustrations in colour
Topics: Data Mining and Knowledge Discovery, Computational Social Sciences, Artificial Intelligence, Database Management, Applications of Graph Theory and Complex Networks