TY - GEN
T1 - When do crowds turn violent? uncovering triggers from media
AU - Ning, Yue
AU - Muthiah, Sathappan
AU - Ramakrishnan, Naren
AU - Rangwala, Huzefa
AU - Mares, David
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/10/24
Y1 - 2018/10/24
N2 - 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.
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.
UR - http://www.scopus.com/inward/record.url?scp=85057329940&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85057329940&partnerID=8YFLogxK
U2 - 10.1109/ASONAM.2018.8508280
DO - 10.1109/ASONAM.2018.8508280
M3 - Conference contribution
AN - SCOPUS:85057329940
T3 - Proceedings of the 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2018
SP - 77
EP - 82
BT - Proceedings of the 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2018
A2 - Tagarelli, Andrea
A2 - Reddy, Chandan
A2 - Brandes, Ulrik
T2 - 10th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2018
Y2 - 28 August 2018 through 31 August 2018
ER -