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  • Conference proceedings
  • © 2014

Predicting Real World Behaviors from Virtual World Data

Editors:

  1. Muhammad Aurangzeb Ahmad

    1. Dept. Computer Science and Engineering, University of Minnesota, Minneapolis, USA

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  2. Cuihua Shen

    1. Emerging Media & Communication Program School of Arts & Humanities, University of Texas at Dallas, Richardson, USA

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  3. Jaideep Srivastava

    1. Department of Computer Science, University of Minnesota, Minneapolis, USA

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  4. Noshir Contractor

    1. Dept. of Communication Studies, Northwestern University, Evanston, USA

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  • 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
  • Includes supplementary material: sn.pub/extras

Part of the book series: Springer Proceedings in Complexity (SPCOM)

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Table of contents (7 papers)

  1. Front Matter

    Pages i-xii
    PDF

  2. On the Problem of Predicting Real World Characteristics from Virtual Worlds

    • Muhammad Aurangzeb Ahmad, Cuihua Shen, Jaideep Srivastava, Noshir Contractor
    Pages 1-18

  3. The Use of Social Science Methods to Predict Player Characteristics from Avatar Observations

    • Carl Symborski, Gary M. Jackson, Meg Barton, Geoffrey Cranmer, Byron Raines, Mary Magee Quinn
    Pages 19-37

  6. Predicting MMO Player Gender from In-Game Attributes Using Machine Learning Models

    • Tracy Kennedy, Rabindra (Robby) Ratan, Komal Kapoor, Nishith Pathak, Dmitri Williams, Jaideep Srivastava
    Pages 69-84

  7. Predicting Links in Human Contact Networks Using Online Social Proximity

    • Annalisa Socievole, Floriano De Rango, Salvatore Marano
    Pages 85-102

  8. Identifying a Typology of Players Based on Longitudinal Game Data

    • Iftekhar Ahmed, Amogh Mahapatra, Marshall Scott Poole, Jaideep Srivastava, Channing Brown
    Pages 103-115

  9. Back Matter

    Pages 117-118
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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.
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Keywords

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Editors and Affiliations

  • Dept. Computer Science and Engineering, University of Minnesota, Minneapolis, USA

    Muhammad Aurangzeb Ahmad

  • Emerging Media & Communication Program School of Arts & Humanities, University of Texas at Dallas, Richardson, USA

    Cuihua Shen

  • Department of Computer Science, University of Minnesota, Minneapolis, USA

    Jaideep Srivastava

  • Dept. of Communication Studies, Northwestern University, Evanston, USA

    Noshir Contractor

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Bibliographic Information

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Access via your institution

Buy it now

eBook USD 39.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book USD 54.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Other ways to access

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