In this paper we leverage a massive attack-focused terrorist database and we design a dynamic bipartite network analysis to examine the structural evolution of terrorists-targets relationships. We introduce two novel measures to jointly assess harmfulness and vulnerability of terrorist and target groups, both at local and global level. Statistical validation using null models provides evidence that the information contained in these measures is new and not included in other variables, thus emphasizing the usefulness of these topological indicators. Finally, a policy-support experiment designed as network dismantling-like drill is proposed to assess the effects of potential attack preventive strategies.

Assessing harmfulness and vulnerability in global bipartite networks of terrorist-target relationships

Paolo Pagnottoni
2022-01-01

Abstract

In this paper we leverage a massive attack-focused terrorist database and we design a dynamic bipartite network analysis to examine the structural evolution of terrorists-targets relationships. We introduce two novel measures to jointly assess harmfulness and vulnerability of terrorist and target groups, both at local and global level. Statistical validation using null models provides evidence that the information contained in these measures is new and not included in other variables, thus emphasizing the usefulness of these topological indicators. Finally, a policy-support experiment designed as network dismantling-like drill is proposed to assess the effects of potential attack preventive strategies.
2022
2022
Bipartite networks; Centrality measures; Networks; Null models; Terrorism network
Spelta, Alessandro; Pecora, Nicoló; Pagnottoni, Paolo
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11383/2170080
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