Predicting Real World Behaviors from Virtual World Data / edited by Muhammad Aurangzeb Ahmad, Cuihua Shen, Jaideep Srivastava, Noshir Contractor.

Format:

Book

Contributor:

Ahmad, Muhammad Aurangzeb, editor.

Shen, Cuihua, editor.

Srivastava, Jaideep, editor.

Contractor, Noshir, editor.

SpringerLink (Online service)

Series:

Computer Science (Springer-11645)

Springer proceedings in complexity 2213-8684

Springer Proceedings in Complexity, 2213-8684

Language:

English

Subjects (All):

Application software.

Sociophysics.

Econophysics.

Social sciences.

Mathematics.

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.

Local Subjects:

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.

Physical Description:

1 online resource (XIV, 118 pages) : 40 illustrations, 27 illustrations in color.

Edition:

First edition 2014.

Contained In:

Springer eBooks

Place of Publication:

Cham : Springer International Publishing : Imprint: Springer, 2014.

System Details:

text file PDF

Summary:

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, et cetera 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.

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.

Other Format:

Printed edition:

ISBN:

978-3-319-07142-8

9783319071428

Access Restriction:

Restricted for use by site license.