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)
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Table of contents(7 papers)
About this book
Editors and Affiliations
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Dept. Computer Science and Engineering, University of Minnesota, Minneapolis, USA
Muhammad Aurangzeb Ahmad
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Emerging Media & Communication Program School of Arts & Humanities, University of Texas at Dallas, Richardson, USA
Cuihua Shen
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Department of Computer Science, University of Minnesota, Minneapolis, USA
Jaideep Srivastava
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Dept. of Communication Studies, Northwestern University, Evanston, USA
Noshir Contractor
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