TY  - BOOK
AU  - Ahmad,Muhammad Aurangzeb
AU  - Shen,Cuihua
AU  - Srivastava,Jaideep
AU  - Contractor,Noshir
ED  - SpringerLink (Online service)
TI  - Predicting Real World Behaviors from Virtual World Data
T2  - Springer Proceedings in Complexity,
SN  - 9783319071428
AV  - QA76.76.A65 
U1  - 004 23
PY  - 2014///
CY  - Cham
PB  - Springer International Publishing, Imprint: Springer
KW  - Computer Science
KW  - Social sciences
KW  - Data processing
KW  - Methodology
KW  - Computer Appl. in Social and Behavioral Sciences
KW  - Socio- and Econophysics, Population and Evolutionary Models
KW  - Methodology of the Social Sciences
KW  - Mathematics in the Humanities and Social Sciences
N1  - Preface -- On The Problem of Predicting Real World Characteristics from Virtual Worlds -- The Use of Social Science Methods to Predict Player Characteristics from Avatar Observations -- Analyzing Effects of Public Communication onto Player Behavior in Massively Multiplayer Online Games -- Identifying User Demographic Traits through Virtual-World Language Use -- Predicting MMO Player Gender from In-Game Attributes using Machine Learning Models -- Predicting Links in Human Contact Networks using Online Social Proximity -- Identifying a Typology of Players Based on Longitudinal Game Data
N2  - This 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. 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
UR  - http://dx.doi.org/10.1007/978-3-319-07142-8
ER  -