University of Oulu

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

Meta-terrorism : identifying linguistic patterns in public discourse after an attack

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Author: Kostakos, Panos1; Nykänen, Markus1; Martinviita, Mikael1;
Organizations: 1Center for Ubiquitous Computing, University of Oulu, Oulu, Finland
Format: article
Version: accepted version
Access: open
Online Access: PDF Full Text (PDF, 0.6 MB)
Persistent link:
Language: English
Published: Institute of Electrical and Electronics Engineers, 2018
Publish Date: 2019-01-22


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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Series: Proceedings of the International Conference on Advances in Social Network Analysis and Mining
ISSN: 2473-991X
ISSN-L: 2473-991X
ISBN: 978-1-5386-6051-5
ISBN Print: 978-1-5386-6052-2
DOI: 10.1109/ASONAM.2018.8508647
Host publication: 2018 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)
Conference: IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Type of Publication: A4 Article in conference proceedings
Field of Science: 112 Statistics and probability
213 Electronic, automation and communications engineering, electronics
Funding: European Commission grant 770469-CUTLER and 645706-GRAGE.
EU Grant Number: (770469) CUTLER - Coastal Urban developmenT through the LEnses of Resiliency
(645706) GRAGE - Grey and green in Europe: elderly living in urban areas
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