TY - GEN
T1 - Modeling Longitudinal Behavior Dynamics Among Extremist Users in Twitter Data
AU - Murugan, Priyadarshini
AU - Karimi, Younes
AU - Squicciarini, Anna
AU - Griffin, Chirstopher
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021
Y1 - 2021
N2 - We use a dynamical systems perspective to analyze a collection of 2.4 million tweets known to originate from ISIS and ISIS-related users. From those users active over a long period of time (i.e., 2+ years), we derive sequences of behaviors and show that the top users cluster into behavioral classes, which naturally describe roles within the ISIS communication structure. We then correlate these classes to the retweet network of the top users showing the relationship between dynamic behavior and retweet network centrality. We use the underlying model to formulate informed hypotheses about the role each user plays. Finally, we show that this model can be used to detect outliers, i.e. accounts that are thought to be outside the ISIS organization but seem to be playing a key communications role and have dynamic behavior consistent with ISIS members.
AB - We use a dynamical systems perspective to analyze a collection of 2.4 million tweets known to originate from ISIS and ISIS-related users. From those users active over a long period of time (i.e., 2+ years), we derive sequences of behaviors and show that the top users cluster into behavioral classes, which naturally describe roles within the ISIS communication structure. We then correlate these classes to the retweet network of the top users showing the relationship between dynamic behavior and retweet network centrality. We use the underlying model to formulate informed hypotheses about the role each user plays. Finally, we show that this model can be used to detect outliers, i.e. accounts that are thought to be outside the ISIS organization but seem to be playing a key communications role and have dynamic behavior consistent with ISIS members.
UR - https://www.scopus.com/pages/publications/85125291954
UR - https://www.scopus.com/pages/publications/85125291954#tab=citedBy
U2 - 10.1109/BigData52589.2021.9671644
DO - 10.1109/BigData52589.2021.9671644
M3 - Conference contribution
AN - SCOPUS:85125291954
T3 - Proceedings - 2021 IEEE International Conference on Big Data, Big Data 2021
SP - 4906
EP - 4914
BT - Proceedings - 2021 IEEE International Conference on Big Data, Big Data 2021
A2 - Chen, Yixin
A2 - Ludwig, Heiko
A2 - Tu, Yicheng
A2 - Fayyad, Usama
A2 - Zhu, Xingquan
A2 - Hu, Xiaohua Tony
A2 - Byna, Suren
A2 - Liu, Xiong
A2 - Zhang, Jianping
A2 - Pan, Shirui
A2 - Papalexakis, Vagelis
A2 - Wang, Jianwu
A2 - Cuzzocrea, Alfredo
A2 - Ordonez, Carlos
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2021 IEEE International Conference on Big Data, Big Data 2021
Y2 - 15 December 2021 through 18 December 2021
ER -