Meta-terrorism : identifying linguistic patterns in public discourse after an attack
Kostakos, Panos; Nykänen, Markus; Martinviita, Mikael; Pandya, Abhinay; Oussalah, Mourad (2018-10-25)
P. Kostakos, M. Nykanen, M. Martinviita, A. Pandya and M. Oussalah, "Meta-Terrorism: Identifying Linguistic Patterns in Public Discourse After an Attack," 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), Barcelona, 2018, pp. 1079-1083. doi: 10.1109/ASONAM.2018.8508647
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https://urn.fi/URN:NBN:fi-fe201901222696
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Abstract
When a terror-related event occurs, there is a surge of traffic on social media comprising of informative messages, emotional outbursts, helpful safety tips, and rumors. It is important to understand the behavior manifested on social media sites to gain a better understanding of how to govern and manage in a time of crisis. We undertook a detailed study of Twitter during two recent terror-related events: the Manchester attacks and the Las Vegas shooting. We analyze the tweets during these periods using (a) sentiment analysis, (b) topic analysis, and (c) fake news detection. Our analysis demonstrates the spectrum of emotions evinced in reaction and the way those reactions spread over the event timeline. Also, with respect to topic analysis, we find “echo chambers”, groups of people interested in similar aspects of the event. Encouraged by our results on these two event datasets, the paper seeks to enable a holistic analysis of social media messages in a time of crisis.
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