Overview
- Highlights recent trends and discoveries in social network analysis
- Showcases research from a multi-disciplinary panel of researchers
- Provides a broad scope of current perspectives on network analysis
- Includes supplementary material: sn.pub/extras
Part of the book series: Lecture Notes in Social Networks (LNSN)
Access this book
Tax calculation will be finalised at checkout
Other ways to access
Table of contents (17 chapters)
-
Front Matter
-
Back Matter
Keywords
About this book
Social network analysis increasingly bridges the discovery of patterns in diverse areas of study as more data becomes available and complex. Yet the construction of huge networks from large data often requires entirely different approaches for analysis including; graph theory, statistics, machine learning and data mining. This work covers frontier studies on social network analysis and mining from different perspectives such as social network sites, financial data, e-mails, forums, academic research funds, XML technology, blog content, community detection and clique finding, prediction of user’s- behavior, privacy in social network analysis, mobility from spatio-temporal point of view, agent technology and political parties in parliament. These topics will be of interest to researchers and practitioners from different disciplines including, but not limited to, social sciences and engineering.
Editors and Affiliations
Bibliographic Information
Book Title: State of the Art Applications of Social Network Analysis
Editors: Fazli Can, Tansel Özyer, Faruk Polat
Series Title: Lecture Notes in Social Networks
DOI: https://doi.org/10.1007/978-3-319-05912-9
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer International Publishing Switzerland 2014
Hardcover ISBN: 978-3-319-05911-2Published: 27 May 2014
Softcover ISBN: 978-3-319-35649-5Published: 10 September 2016
eBook ISBN: 978-3-319-05912-9Published: 14 May 2014
Series ISSN: 2190-5428
Series E-ISSN: 2190-5436
Edition Number: 1
Number of Pages: XII, 372
Number of Illustrations: 43 b/w illustrations, 94 illustrations in colour
Topics: Data Mining and Knowledge Discovery, Computational Intelligence, Applications of Graph Theory and Complex Networks