{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T04:52:01Z","timestamp":1750308721621,"version":"3.41.0"},"reference-count":25,"publisher":"Association for Computing Machinery (ACM)","issue":"3","license":[{"start":{"date-parts":[[2013,6,1]],"date-time":"2013-06-01T00:00:00Z","timestamp":1370044800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"DOI":"10.13039\/501100003977","name":"Israel Science Foundation","doi-asserted-by":"publisher","award":["1357\/07"],"award-info":[{"award-number":["1357\/07"]}],"id":[{"id":"10.13039\/501100003977","id-type":"DOI","asserted-by":"publisher"}]},{"name":"IMOD and ISF","award":["1357\/07"],"award-info":[{"award-number":["1357\/07"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Trans. Intell. Syst. Technol."],"published-print":{"date-parts":[[2013,6]]},"abstract":"<jats:p>\n            The ability to model and reason about the potential violence level of a demonstration is important to the police decision making process. Unfortunately, existing knowledge regarding demonstrations is composed of partial qualitative descriptions without complete and precise numerical information. In this article we describe a first attempt to use qualitative reasoning techniques to model demonstrations. To our knowledge, such techniques have never been applied to modeling and reasoning regarding crowd behaviors, nor in particular demonstrations. We develop qualitative models consistent with the partial, qualitative social science literature, allowing us to model the interactions between different factors that influence violence in demonstrations. We then utilize qualitative simulation to predict the potential eruption of violence, at various levels, based on a description of the demographics, environmental settings, and police responses. We incrementally present and compare three such qualitative models. 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 provides good results. We also examine whether a popular machine learning algorithm (decision tree learning) can be used. While the results show that the decision trees provide improved predictions, we show that the QR models can be more sensitive to changes, and can account for\n            <jats:italic>what-if<\/jats:italic>\n            scenarios, in contrast to decision trees. Moreover, we introduce a novel analysis algorithm that analyzes the QR simulations, to automatically determine the factors that are most important in influencing the outcome in specific real-world demonstrations. We show that the algorithm identifies factors that correspond to experts' analysis of these events.\n          <\/jats:p>","DOI":"10.1145\/2483669.2483687","type":"journal-article","created":{"date-parts":[[2013,7,1]],"date-time":"2013-07-01T12:27:28Z","timestamp":1372681648000},"page":"1-21","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":3,"title":["Using qualitative reasoning for social simulation of crowds"],"prefix":"10.1145","volume":"4","author":[{"given":"Natalie","family":"Fridman","sequence":"first","affiliation":[{"name":"The MAVERICK Group and Bar Ilan University, Israel"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Gal A.","family":"Kaminka","sequence":"additional","affiliation":[{"name":"The MAVERICK Group and Bar Ilan University, Israel"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2013,7]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.5555\/1756006.1953016"},{"key":"e_1_2_1_2_1","first-page":"1","article-title":"Qualitative modeling and simulation of socio-economic phenomena","volume":"1","author":"Brajnik G.","year":"1998","journal-title":"J. Artif. Soc. Social Simul."},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ecoinf.2009.09.009"},{"key":"e_1_2_1_4_1","doi-asserted-by":"crossref","unstructured":"Bredeweg B. and Salles P. 2009. Mediating conceptual knowledge using qualitative reasoning. In Handbook of Ecological Modelling and Informatics S. Jrgensen T.-S. Chon and F. E. Recknagel Eds. Wit Press Southampton UK 351--398.  Bredeweg B. and Salles P. 2009. Mediating conceptual knowledge using qualitative reasoning. In Handbook of Ecological Modelling and Informatics S. Jrgensen T.-S. Chon and F. E. Recknagel Eds. Wit Press Southampton UK 351--398.","DOI":"10.2495\/978-1-84564-207-5\/19"},{"key":"e_1_2_1_5_1","unstructured":"Carmeli A. and Ravid-Yamin I. 2006. Research report on the subject of crowd events and public order. Tech. rep. Ministry of Public Security Bureau of the Chief Scientist.  Carmeli A. and Ravid-Yamin I. 2006. Research report on the subject of crowd events and public order. Tech. rep. Ministry of Public Security Bureau of the Chief Scientist."},{"volume-title":"CRC Handbook of Computer Science and Engineering","author":"Forbus K. D.","key":"e_1_2_1_6_1"},{"volume-title":"Proceedings of the 19th International Qualitative Reasoning Workshop.","author":"Forbus K. D.","key":"e_1_2_1_7_1"},{"volume-title":"Proceedings of the 22nd AAAI Conference on Artificial Intelligence (AAAI'07)","author":"Fridman N.","key":"e_1_2_1_8_1"},{"key":"e_1_2_1_9_1","unstructured":"Gilbert N. and Troitzsch K. G. 2005. Simulation for the Social Scientist. Open University Press.   Gilbert N. and Troitzsch K. G. 2005. Simulation for the Social Scientist. Open University Press."},{"volume-title":"Studies in Fuzziness and Soft Computing","author":"Glykas M.","key":"e_1_2_1_10_1"},{"key":"e_1_2_1_11_1","first-page":"3","article-title":"Clustering and fighting in two-party crowds: Simulating the approach-avoidance conflict","volume":"4","author":"Jager W.","year":"2001","journal-title":"J. Artif. Soc. Social Simul."},{"volume-title":"Proceedings of the Qualitative Reasoning Workshop.","author":"Kamps J.","key":"e_1_2_1_12_1"},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0020-7373(86)80040-2"},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1016\/0005-1098(89)90099-X"},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1007\/BF02686734"},{"key":"e_1_2_1_16_1","unstructured":"McPhail C. 1991. The Myth of the Madding Crowd. Aldine de Gruyter New York.  McPhail C. 1991. The Myth of the Madding Crowd. Aldine de Gruyter New York."},{"key":"e_1_2_1_17_1","unstructured":"Mitchell T. M. 1997. Machine Learning. McGraw-Hill.   Mitchell T. M. 1997. Machine Learning. McGraw-Hill."},{"volume-title":"Proceedings of the 8th European Conference on Principles and Practice of Knowledge Discovery in Databases (PKDD'04)","author":"Mozina M.","key":"e_1_2_1_18_1"},{"key":"e_1_2_1_19_1","first-page":"1","article-title":"Simulating correctional disturbances: The application of organization control theory to correctional organizations via computer simulation","volume":"2","author":"Patrick S.","year":"1999","journal-title":"J. Artif. Soc. Social Simul."},{"key":"e_1_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.ecolmodel.2005.11.014"},{"key":"e_1_2_1_21_1","doi-asserted-by":"publisher","DOI":"10.1177\/0049124199027004001"},{"key":"e_1_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1177\/a010563"},{"key":"e_1_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1093\/sf\/76.2.357"},{"key":"e_1_2_1_24_1","unstructured":"Wander J. 2000. Modelling consumer behavior. Ph.D. thesis University of Groningen The Netherlands.  Wander J. 2000. Modelling consumer behavior. Ph.D. thesis University of Groningen The Netherlands."},{"key":"e_1_2_1_25_1","unstructured":"Wikipedia: The Free Encyclopeida. 2010. Category: Demonstrations (hebrew).  Wikipedia: The Free Encyclopeida. 2010. Category: Demonstrations (hebrew)."}],"container-title":["ACM Transactions on Intelligent Systems and Technology"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/2483669.2483687","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/2483669.2483687","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T20:14:36Z","timestamp":1750277676000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/2483669.2483687"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2013,6]]},"references-count":25,"journal-issue":{"issue":"3","published-print":{"date-parts":[[2013,6]]}},"alternative-id":["10.1145\/2483669.2483687"],"URL":"https:\/\/doi.org\/10.1145\/2483669.2483687","relation":{},"ISSN":["2157-6904","2157-6912"],"issn-type":[{"type":"print","value":"2157-6904"},{"type":"electronic","value":"2157-6912"}],"subject":[],"published":{"date-parts":[[2013,6]]},"assertion":[{"value":"2011-06-01","order":0,"name":"received","label":"Received","group":{"name":"publication_history","label":"Publication History"}},{"value":"2012-01-01","order":1,"name":"accepted","label":"Accepted","group":{"name":"publication_history","label":"Publication History"}},{"value":"2013-07-01","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}