Predicting Real World Behaviors from Virtual World Data

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...

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Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Ahmad, Muhammad Aurangzeb (Editor ), Shen, Cuihua (Editor ), Srivastava, Jaideep (Editor ), Contractor, Noshir (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Cham : Springer International Publishing : Imprint: Springer, 2014.
Edición:1st ed. 2014.
Colección:Springer Proceedings in Complexity,
Temas:
Social sciences-Data processing.
System theory.
Sociology-Methodology.
Mathematics.
Social sciences.
Computer Application in Social and Behavioral Sciences.
Complex Systems.
Sociological Methods.
Mathematics in the Humanities and Social Sciences.
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • 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.

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