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.
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We have created a single “Al Qaeda” group category summing together all the events plotted by the following factions present in the dataset, which are part of the greater Al Qaeda network: Al-Qaida, Al-Qaida in Iraq, Al-Qaida in Saudi Arabia, Al-Qaida in the Arabian Peninsula (AQAP), Al-Qaida in Yemen, Al Qaida in Lebanon, Al-Qaida in the Islamic Maghreb, Al-Qaida in the Indian Subcontinent, Islambouli Brigades of Al-Qaida, Secret Organization of Al-Qaida in Europe, Al-Qaida Organization for Jihad in Sweden, Al-Qaida Network for Southwestern Khulna Division, Jadid Al-Qaida Banglades (JAQB), Al-Qaida Kurdish Battalions.
It is worth specifying that in the analyses, events will be ordered temporally but without taking into account the actual delta between attacks. This means that there is no difference between two attacks plotted within a range of 4 days and the other two attacks plotted within a range of 5 months. Additionally, when two or more attacks are plotted on the same day, we order them by the eventid variable included in the original dataset, assuming that the information coded in the variable provides a more robust ordering criterion than pure random distribution.
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The authors would like to thank the two anonymous reviewers for their comments on a previous version of the paper. This work was supported in part by the Office of Naval Research under the Multidisciplinary University Research Initiatives (MURI) Program award number N000141712675, Near Real Time Assessment of Emergent Complex Systems of Confederates, the Minerva program under grant number N000141512797, Dynamic Statistical Network Informatics, and by the center for Computational Analysis of Social and Organizational Systems (CASOS). The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the ONR or the US government.
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Campedelli, G.M., Bartulovic, M. & Carley, K.M. Pairwise similarity of jihadist groups in target and weapon transitions. J Comput Soc Sc 2, 245–270 (2019). https://doi.org/10.1007/s42001-019-00046-8
- Transition networks
- Normalized transition similarity
- Event sequences