Predicting Real World Behaviors from Virtual World Data
Editors: Ahmad, M.A., Shen, C., Srivastava, J., Contractor, N. (Eds.)
Free Preview- 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
Buy this book
- About this book
-
There is a growing body of literature that focuses on the similarities and differences between how people behave in the offline world vs. how they behave in these virtual environments. Data mining has aided in discovering interesting insights with respect to how people behave in these virtual environments. The book addresses prediction, mining and analysis of offline characteristics and behaviors from online data and vice versa. Each chapter will focus on a different aspect of virtual worlds to real world prediction e.g., demographics, personality, location, etc.
- Table of contents (7 chapters)
-
-
On the Problem of Predicting Real World Characteristics from Virtual Worlds
Pages 1-18
-
The Use of Social Science Methods to Predict Player Characteristics from Avatar Observations
Pages 19-37
-
Analyzing Effects of Public Communication onto Player Behavior in Massively Multiplayer Online Games
Pages 39-56
-
Identifying User Demographic Traits Through Virtual-World Language Use
Pages 57-67
-
Predicting MMO Player Gender from In-Game Attributes Using Machine Learning Models
Pages 69-84
-
Table of contents (7 chapters)
- Download Preface 1 PDF (132.2 KB)
- Download Sample pages 1 PDF (290.8 KB)
- Download Table of contents PDF (102 KB)
Recommended for you
Bibliographic Information
- 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
- Copyright
- 2014
- Publisher
- Springer International Publishing
- Copyright Holder
- Springer International Publishing Switzerland
- eBook ISBN
- 978-3-319-07142-8
- DOI
- 10.1007/978-3-319-07142-8
- Hardcover ISBN
- 978-3-319-07141-1
- Softcover ISBN
- 978-3-319-34849-0
- Series ISSN
- 2213-8684
- Edition Number
- 1
- Number of Pages
- XIV, 118
- Number of Illustrations
- 13 b/w illustrations, 27 illustrations in colour
- Topics
