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.
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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.
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This work was supported by the TENSOR (H2020-700024) and the PROPHETS projects (H2020-786894), both funded by the European Commission.
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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
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