When do crowds turn violent? uncovering triggers from media

Yue Ning; Sathappan Muthiah; Naren Ramakrishnan; Huzefa Rangwala; David Mares

doi:10.1109/ASONAM.2018.8508280

When do crowds turn violent? uncovering triggers from media

Yue Ning
, Sathappan Muthiah
, Naren Ramakrishnan
, Huzefa Rangwala
, David Mares

Department of Computer Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

3 Scopus citations

Abstract

Mass gatherings often underlie civil disobedience activities and as such run the risk of turning violent, causing damage to both property and people. While civil unrest is a rather common phenomenon, only a small subset of them involve crowds turning violent. How can we distinguish which events are likely to lead to violence? Using articles gathered from thousands of online news sources, we study a two-level multi-instance learning formulation, CrowdForecaster, tailored to forecast violent crowd behavior, specifically violent protests. Using data from five countries in Latin America, we demonstrate not just the predictive utility of our approach, but also its effectiveness in discovering triggering factors, especially in uncovering how and when crowd behavior begets violence.

Original language	English
Title of host publication	Proceedings of the 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2018
Editors	Andrea Tagarelli, Chandan Reddy, Ulrik Brandes
Pages	77-82
Number of pages	6
ISBN (Electronic)	9781538660515
DOIs	https://doi.org/10.1109/ASONAM.2018.8508280
State	Published - 24 Oct 2018
Event	10th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2018 - Barcelona, Spain Duration: 28 Aug 2018 → 31 Aug 2018

Publication series

Name	Proceedings of the 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2018

Conference

Conference	10th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2018
Country/Territory	Spain
City	Barcelona
Period	28/08/18 → 31/08/18

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 16 Peace, Justice and Strong Institutions

Access to Document

10.1109/ASONAM.2018.8508280

Cite this

Ning, Y., Muthiah, S., Ramakrishnan, N., Rangwala, H., & Mares, D. (2018). When do crowds turn violent? uncovering triggers from media. In A. Tagarelli, C. Reddy, & U. Brandes (Eds.), Proceedings of the 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2018 (pp. 77-82). Article 8508280 (Proceedings of the 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2018). https://doi.org/10.1109/ASONAM.2018.8508280

Ning, Yue ; Muthiah, Sathappan ; Ramakrishnan, Naren et al. / When do crowds turn violent? uncovering triggers from media. Proceedings of the 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2018. editor / Andrea Tagarelli ; Chandan Reddy ; Ulrik Brandes. 2018. pp. 77-82 (Proceedings of the 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2018).

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title = "When do crowds turn violent? uncovering triggers from media",

abstract = "Mass gatherings often underlie civil disobedience activities and as such run the risk of turning violent, causing damage to both property and people. While civil unrest is a rather common phenomenon, only a small subset of them involve crowds turning violent. How can we distinguish which events are likely to lead to violence? Using articles gathered from thousands of online news sources, we study a two-level multi-instance learning formulation, CrowdForecaster, tailored to forecast violent crowd behavior, specifically violent protests. Using data from five countries in Latin America, we demonstrate not just the predictive utility of our approach, but also its effectiveness in discovering triggering factors, especially in uncovering how and when crowd behavior begets violence.",

author = "Yue Ning and Sathappan Muthiah and Naren Ramakrishnan and Huzefa Rangwala and David Mares",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 10th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2018 ; Conference date: 28-08-2018 Through 31-08-2018",

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Ning, Y, Muthiah, S, Ramakrishnan, N, Rangwala, H & Mares, D 2018, When do crowds turn violent? uncovering triggers from media. in A Tagarelli, C Reddy & U Brandes (eds), Proceedings of the 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2018., 8508280, Proceedings of the 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2018, pp. 77-82, 10th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2018, Barcelona, Spain, 28/08/18. https://doi.org/10.1109/ASONAM.2018.8508280

When do crowds turn violent? uncovering triggers from media. / Ning, Yue; Muthiah, Sathappan; Ramakrishnan, Naren et al.
Proceedings of the 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2018. ed. / Andrea Tagarelli; Chandan Reddy; Ulrik Brandes. 2018. p. 77-82 8508280 (Proceedings of the 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2018).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

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AB - Mass gatherings often underlie civil disobedience activities and as such run the risk of turning violent, causing damage to both property and people. While civil unrest is a rather common phenomenon, only a small subset of them involve crowds turning violent. How can we distinguish which events are likely to lead to violence? Using articles gathered from thousands of online news sources, we study a two-level multi-instance learning formulation, CrowdForecaster, tailored to forecast violent crowd behavior, specifically violent protests. Using data from five countries in Latin America, we demonstrate not just the predictive utility of our approach, but also its effectiveness in discovering triggering factors, especially in uncovering how and when crowd behavior begets violence.

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Ning Y, Muthiah S, Ramakrishnan N, Rangwala H, Mares D. When do crowds turn violent? uncovering triggers from media. In Tagarelli A, Reddy C, Brandes U, editors, Proceedings of the 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2018. 2018. p. 77-82. 8508280. (Proceedings of the 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2018). doi: 10.1109/ASONAM.2018.8508280

When do crowds turn violent? uncovering triggers from media

Abstract

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UN SDGs

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