Predicting Real World Behaviors from Virtual World Data

• Corporate Author: SpringerLink (Online service)
• Other Authors: Ahmad, Muhammad Aurangzeb (Editor), Shen, Cuihua (Editor), Srivastava, Jaideep (Editor), Contractor, Noshir (Editor)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2014.
• Series: Springer Proceedings in Complexity,
• Subjects: Computer science.; Application software.; Mathematics.; Social sciences.; Sociophysics.; Econophysics.; Computer Science.; Computer Appl. in Social and Behavioral Sciences.; Socio- and Econophysics, Population and Evolutionary Models.; Methodology of the Social Sciences.; Mathematics in the Humanities and Social Sciences.

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...

Table of Contents:

• 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.