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Identifying Terrorism-Related Key Actors in Multidimensional Social Networks

  • George KalpakisEmail author
  • Theodora Tsikrika
  • Stefanos Vrochidis
  • Ioannis Kompatsiaris
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11296)

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.

Keywords

Multidimensional social networks Key actors Centrality measures Online terrorism 

Notes

Acknowledgements

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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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • George Kalpakis
    • 1
    Email author
  • Theodora Tsikrika
    • 1
  • Stefanos Vrochidis
    • 1
  • Ioannis Kompatsiaris
    • 1
  1. 1.Information Technologies InstituteCentre for Research and Technology HellasThermi, ThessalonikiGreece

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