Predicting demonstrations' violence level using qualitative reasoning

Natalie Fridman, Tomer Zilberstein, Gal A. Kaminka

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper we describe a method for modeling social behavior of large groups, and apply it to the problem of predicting potential violence during demonstrations. We use qualitative reasoning techniques which to our knowledge have never been applied to modeling crowd behaviors, nor in particular to demonstrations. Such modeling may not only contribute to the police decision making process, but can also provide a great opportunity to test existing theories in social science. We incrementally present and compare three qualitative models, based on social science theories. The results show that while two of these models fail to predict the outcomes of real-world events reported and analyzed in the literature, one model is successful. We believe that this demonstrates the efficacy of qualitative reasoning in the development and testing of social sciences theories.

Original languageEnglish
Title of host publicationSocial Computing, Behavioral-Cultural Modeling and Prediction - 4th International Conference, SBP 2011, Proceedings
Pages42-50
Number of pages9
DOIs
StatePublished - 2011
Event4th International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction, SBP 2011 - College Park, MD, United States
Duration: 29 Mar 201131 Mar 2011

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6589 LNCS

Conference

Conference4th International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction, SBP 2011
Country/TerritoryUnited States
CityCollege Park, MD
Period29/03/1131/03/11

Keywords

  • Demonstrations
  • Qualitative reasoning
  • Social Simulation

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • General Computer Science

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