TY - GEN
T1 - Identification and characterization of cyberbullying dynamics in an online social network
AU - Squicciarini, A.
AU - Rajtmajer, S.
AU - Liu, Y.
AU - Griffin, C.
N1 - Funding Information:
VIII. ACKNOWLEDGEMENTS Portions of Dr. Griffin's, Dr. Rajtmajer's and Dr. Squicciarini's work were supported by the Army Research Office grant W911NF-13-1-0271. Portions of Dr. Griffins work were additionally supported by the Army Research Office grant W911NF-11-1-0487.
Publisher Copyright:
© 2015 ACM.
PY - 2015/8/25
Y1 - 2015/8/25
N2 - Cyberbullying is an increasingly prevalent phenomenon impacting young adults. In this paper, we present a study on both detecting cyberbullies in online social networks and identifying the pairwise interactions between users through which the influence of bullies seems to spread. In particular, we investigate the role of user demographics and social network features in predicting how users will respond to a cyberbullying comment. We characterize the influencer/influenced relationship by which a user who has no history of abuse observes a peer engaging in bullying and follows suit. To our knowledge, this is the first effort modeling peer pressure and social dynamics with analytical models. We validate our models on two distinct social network datasets, totalling over 16, 000 posts. Our results offer insight into the dynamics of bullying and confirm social theories on the power of peer groups in the cyberworld. A full version of this paper is available on arXiv.org.
AB - Cyberbullying is an increasingly prevalent phenomenon impacting young adults. In this paper, we present a study on both detecting cyberbullies in online social networks and identifying the pairwise interactions between users through which the influence of bullies seems to spread. In particular, we investigate the role of user demographics and social network features in predicting how users will respond to a cyberbullying comment. We characterize the influencer/influenced relationship by which a user who has no history of abuse observes a peer engaging in bullying and follows suit. To our knowledge, this is the first effort modeling peer pressure and social dynamics with analytical models. We validate our models on two distinct social network datasets, totalling over 16, 000 posts. Our results offer insight into the dynamics of bullying and confirm social theories on the power of peer groups in the cyberworld. A full version of this paper is available on arXiv.org.
UR - http://www.scopus.com/inward/record.url?scp=84962597182&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84962597182&partnerID=8YFLogxK
U2 - 10.1145/2808797.2809398
DO - 10.1145/2808797.2809398
M3 - Conference contribution
AN - SCOPUS:84962597182
T3 - Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015
SP - 280
EP - 285
BT - Proceedings of the 2015 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015
A2 - Pei, Jian
A2 - Tang, Jie
A2 - Silvestri, Fabrizio
PB - Association for Computing Machinery, Inc
T2 - IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2015
Y2 - 25 August 2015 through 28 August 2015
ER -