Overview
- Gathers insights from different disciplines like data mining, behavioral modeling, ethnography to connect the online with the offline world
- Features data-driven and theory-driven techniques for predicting people’s behavior in the real world
- Provides a framework for doing predictive modeling from virtual worlds to the real world and the efficacy of such predictions
- Includes supplementary material: sn.pub/extras
Part of the book series: Springer Proceedings in Complexity (SPCOM)
Access this book
Tax calculation will be finalised at checkout
Other ways to access
About this book
Similar content being viewed by others
Keywords
Table of contents (7 papers)
Editors and Affiliations
Bibliographic Information
Book Title: Predicting Real World Behaviors from Virtual World Data
Editors: Muhammad Aurangzeb Ahmad, Cuihua Shen, Jaideep Srivastava, Noshir Contractor
Series Title: Springer Proceedings in Complexity
DOI: https://doi.org/10.1007/978-3-319-07142-8
Publisher: Springer Cham
eBook Packages: Computer Science, Computer Science (R0)
Copyright Information: Springer International Publishing Switzerland 2014
Hardcover ISBN: 978-3-319-07141-1Published: 07 August 2014
Softcover ISBN: 978-3-319-34849-0Published: 24 September 2016
eBook ISBN: 978-3-319-07142-8Published: 24 July 2014
Series ISSN: 2213-8684
Series E-ISSN: 2213-8692
Edition Number: 1
Number of Pages: XIV, 118
Number of Illustrations: 13 b/w illustrations, 27 illustrations in colour
Topics: Computer Appl. in Social and Behavioral Sciences, Data-driven Science, Modeling and Theory Building, Methodology of the Social Sciences, Mathematics in the Humanities and Social Sciences