Abstract
Identifying terrorism-related key actors in social media is of vital significance for law enforcement agencies and social media organizations in their effort to counter terrorism-related online activities. This work proposes a novel framework for the identification of key actors in multidimensional social networks formed by considering several different types of user relationships/interactions in social media. The framework is based on a mechanism which maps the multidimensional network to a single-layer network, where several centrality measures can then be employed for detecting the key actors. The effectiveness of the proposed framework for each centrality measure is evaluated by using well-established precision-oriented evaluation metrics against a ground truth dataset, and the experimental results indicate the promising performance of our key actor identification framework.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Notes
- 1.
A mention represents a simple reference to a user within a tweet.
- 2.
A retweet is a re-post of a tweet.
- 3.
Twitter followers are users who follow or subscribe to another user’s tweets. A user’s following list contains all the users they follow on Twitter, whereas their followers list contains the users who follow them.
References
Aparicio, S., Villazón-Terrazas, J., Álvarez, G.: A model for scale-free networks: application to twitter. Entropy 17(8), 5848–5867 (2015)
Azaza, L., Kirgizov, S., Savonnet, M., Leclercq, E., Faiz, R.: Influence assessment in twitter multi-relational network. In: 2015 11th International Conference on Signal-Image Technology & Internet-Based Systems (SITIS), pp. 436–443. IEEE (2015)
Barabási, A.L., Albert, R.: Emergence of scaling in random networks. Science 286(5439), 509–512 (1999)
Boccaletti, S., et al.: The structure and dynamics of multilayer networks. Phys. Rep. 544(1), 1–122 (2014)
Bonacich, P., Lloyd, P.: Eigenvector-like measures of centrality for asymmetric relations. Soc. Netw. 23(3), 191 (2001)
Brandes, U.: A faster algorithm for betweenness centrality. J. Math. Sociol. 25(2), 163–177 (2001)
Brin, S., Page, L.: Reprint of: the anatomy of a large-scale hypertextual web search engine. Comput. Netw. 56(18), 3825–3833 (2012)
Choudhary, P., Singh, U.: A survey on social network analysis for counter-terrorism. Int. J. Comput. Appl. 112(9), 24–29 (2015)
Coscia, M.: Multidimensional network analysis. Ph. D. thesis, Universitá Degli Studi Di Pisa, Dipartimento di Informatica (2012)
Freeman, L.C.: Centrality in social networks conceptual clarification. Soc. Netw. 1(3), 215–239 (1978)
Gialampoukidis, I., Kalpakis, G., Tsikrika, T., Papadopoulos, S., Vrochidis, S.: Kompatsiaris, I.: Detection of terrorism-related twitter communities using centrality scores. In: Proceedings of the 2nd International Workshop on Multimedia Forensics and Security, pp. 21–25. ACM (2017)
Gialampoukidis, I., Kalpakis, G., Tsikrika, T., Vrochidis, S., Kompatsiaris, I.: Key player identification in terrorism-related social media networks using centrality measures. In: 2016 European Intelligence and Security Informatics Conference (EISIC), pp. 112–115. IEEE (2016)
Jabeur, L.B., Tamine, L., Boughanem, M.: Active microbloggers: identifying influencers, leaders and discussers in microblogging networks. In: Calderón-Benavides, L., González-Caro, C., Chávez, E., Ziviani, N. (eds.) SPIRE 2012. LNCS, vol. 7608, pp. 111–117. Springer, Heidelberg (2012). https://doi.org/10.1007/978-3-642-34109-0_12
Li, L., Alderson, D., Doyle, J.C., Willinger, W.: Towards a theory of scale-free graphs: definition, properties, and implications. Internet Math. 2(4), 431–523 (2005)
Nie, T., Guo, Z., Zhao, K., Lu, Z.M.: Using mapping entropy to identify node centrality in complex networks. Phys. A Stat. Mech. Appl. 453, 290–297 (2016)
Opsahl, T., Agneessens, F., Skvoretz, J.: Node centrality in weighted networks: generalizing degree and shortest paths. Soc. Netw. 32(3), 245–251 (2010)
Thompson, R.L.: Radicalization and the use of social media. J. Strat. Secur. 4(4), 167 (2011)
Zhaoyun, D., Yan, J., Bin, Z., Yi, H.: Mining topical influencers based on the multi-relational network in micro-blogging sites. China Commun. 10(1), 93–104 (2013)
Acknowledgements
This work was supported by the TENSOR (H2020-700024) and the PROPHETS projects (H2020-786894), both funded by the European Commission.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2019 Springer Nature Switzerland AG
About this paper
Cite this paper
Kalpakis, G., Tsikrika, T., Vrochidis, S., Kompatsiaris, I. (2019). Identifying Terrorism-Related Key Actors in Multidimensional Social Networks. In: Kompatsiaris, I., Huet, B., Mezaris, V., Gurrin, C., Cheng, WH., Vrochidis, S. (eds) MultiMedia Modeling. MMM 2019. Lecture Notes in Computer Science(), vol 11296. Springer, Cham. https://doi.org/10.1007/978-3-030-05716-9_8
Download citation
DOI: https://doi.org/10.1007/978-3-030-05716-9_8
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-05715-2
Online ISBN: 978-3-030-05716-9
eBook Packages: Computer ScienceComputer Science (R0)