Social Computing, Behavioral Modeling, and Prediction

  • Huan Liu
  • John J. Salerno
  • Michael J. Young

Table of contents

  1. Front Matter
    Pages I-XVII
  2. Michael Hechter
    Pages 19-24
  3. Rebecca Goolsby
    Pages 25-25
  4. Aaron Mannes, Mary Michael, Amy Pate, Amy Sliva, V.S. Subrahmanian, Jonathan Wilkenfeld
    Pages 37-45
  5. Norman D. Geddes, Michele L. Atkinson
    Pages 46-56
  6. A.H. Levis, Smriti K. Kansal, A.E. Olmez, Ashraf M. AbuSharekh
    Pages 57-68
  7. Nathan Eagle, Alex (Sandy) Pentland, David Lazer
    Pages 79-88
  8. David J. Robinson, Vincent H. Berk, George V. Cybenko
    Pages 100-109
  9. Robert Savell, George Cybenko
    Pages 110-119
  10. Muhammad Aurangzeb Ahmad, Jaideep Srivastava
    Pages 120-128
  11. Xiaohui Cui, Laura L. Pullum, Jim Treadwell, Robert M. Patton, Thomas E. Potok
    Pages 141-150
  12. Steven Loscalzo, Lei Yu
    Pages 151-159
  13. Santi Phithakkitnukoon, Husain Husna, Ram Dantu
    Pages 160-167
  14. Karsten Steinhaeuser, Nitesh V. Chawla
    Pages 168-175

About these proceedings

Introduction

Social computing concerns the study of social behavior and context based on computational systems. Behavioral modeling reproduces the social behavior, and allows for experimenting, scenario planning, and deep understanding of behavior, patterns, and potential outcomes. The pervasive use of computer and Internet technologies creates an unprecedented environment where people can share opinions and experiences, exchange ideas, offer suggestions and advice, debate and even conduct experiments. Social computing facilitates behavioral modeling in model building, analysis, pattern mining, anticipation, and prediction.

This unique volume presents material from the first interdisciplinary workshop focused on employing social computing for behavioral modeling and prediction. The book provides a platform for disseminating results and developing new concepts and methodologies aimed at advancing and deepening our understanding of social and behavioral computing to aid critical decision making. The contributions incorporate views from government, industry and academia and they address research problems arising from pressing demands in the real world.

Researchers, practitioners and graduate students from sociology, behavioral and computer science, psychology, cultural study, information systems, and operations research are certain to find this a fascinating and essential resource.

Keywords

Clustering Internet Operations Research Social computing behavioral modeling and prediction calculus classification computational cultural study group profiling and interaction modeling optimization simulation with social media

Editors and affiliations

  • Huan Liu
    • 1
  • John J. Salerno
  • Michael J. Young
  1. 1.Ira A. Fulton School of EngineeringArizona State UniversityTempeU.S.A.

Bibliographic information

  • DOI https://doi.org/10.1007/978-0-387-77672-9
  • Copyright Information Springer Science+Business Media, LLC 2008
  • Publisher Name Springer, Boston, MA
  • eBook Packages Computer Science
  • Print ISBN 978-0-387-77671-2
  • Online ISBN 978-0-387-77672-9
  • About this book