Pairwise similarity of jihadist groups in target and weapon transitions

Gian Maria Campedelli, Mihovil Bartulovic, Kathleen M. Carley

Research output: Contribution to journalArticlepeer-review

Abstract

Tactical decisions made by jihadist groups can have extremely negative impacts on societies. Studying the characteristics of their attacks over time is therefore crucial to extract relevant knowledge on their operational choices. In light of this, the present study employs transition networks to construct trails and analyze the behavioral patterns of the world’s five most active jihadist groups using open access data on terror attacks from 2001 to 2016. Within this frame, we propose Normalized Transition Similarity (NTS), a coefficient that captures groups’ pairwise similarity in terms of transitions between different temporally ordered sequences of states. For each group, these states respectively map attacked targets, employed weapons, and targets and weapons combined together with respect to the entire sequence of attacks. Analyses show a degree of stability of results among a number of pairs of groups across all trails. With this regard, Al Qaeda and Al Shabaab exhibit the highest NTS scores, while the Taliban and Al Qaeda prove to be the most different groups overall. Finally, potential policy implications and future work directions are also discussed.
Original languageEnglish
Pages (from-to)1-26
Number of pages26
JournalJOURNAL OF COMPUTATIONAL SOCIAL SCIENCE
Volume2019
DOIs
Publication statusPublished - 2019

Keywords

  • Reti complesse, sequenze di eventi, terrorismo, jihad
  • Transition networks, Terrorism, Normalized transition similarity, Event sequences, Security

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