© 2009

Social Computing and Behavioral Modeling

  • Michael J. Young
  • John Salerno
  • Huan  Liu
  • Integrates an interdisciplinary audience comprised of researchers, practitioners, and graduate students from social science, behavioral science, computer science, psychology, cultural study, information systems, and operations research

  • Incorporates views from government, industry, and academia

Conference proceedings

Table of contents

  1. Front Matter
    Pages 1-14
  2. Denise Anthony, Tristan Henderson, James Kitts
    Pages 1-8
  3. Nadya Belov, Michael K. Martin, Jeff Patti, Jeff Reminga, Angela Pawlowski, Kathleen M. Carley
    Pages 1-9
  4. Michael Bernard, George Backus, Matthew Glickman, Charles Gieseler, Russel Waymire
    Pages 1-8
  5. Georgiy V. Bobashev, Robert J. Morris, William A. Zule, Andrei V. Borshchev, Lee Hoffer
    Pages 1-6
  6. Mark A. Ehlen, Michael L. Bernard, Andrew J. Schol
    Pages 1-9
  7. Anthony J. Ford, Alice M. Mulvehill
    Pages 1-8
  8. Vadas Gintautas, Aric Hagberg, Luís M. A. Bettencourt
    Pages 1-9
  9. Michael Hechter, Nika Kabiri
    Pages 1-11
  10. Masahiro Kimura, Kazumi Saito, Ryohei Nakano, Hiroshi Motoda
    Pages 1-8
  11. Faisal Mansoor, Abbas K. Zaidi, Lee Wagenhals, Alexander H. Levis
    Pages 1-9

About these proceedings


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 volume presents material from the second 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 from this year’s conference, incorporating views from government, industry and academia, address themes such as:

  • social network analysis
  • modeling
  • machine learning and data mining
  • social behaviors and social order
  • public health
  • cultural aspects
  • trust, privacy, and intention
  • opinion, preference, influence, and diffusion
  • extreme events
  • assessment and validation
  • effects and search

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





Computer Evaluation Pattern Mining Sage classification computational cultural study group profiling and interaction modeling simulation with social media

Editors and affiliations

  • Michael J. Young
  • John Salerno
  • Huan  Liu

There are no affiliations available

Bibliographic information

Industry Sectors
IT & Software
Consumer Packaged Goods
Finance, Business & Banking
Energy, Utilities & Environment
Oil, Gas & Geosciences