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islamic_state_europe — Islamic State network in Europe (2014-2016)

Description

Networks of the individuals involved in the terrorist attacks carried out in Europe by the Islamic State (IS) network that perpetrated the attacks of November 13, 2015 in Paris and of March 22, 2016 in Brussels (called IS in Europe, or IS-E, by the authors), compiled by Alexander Gutfraind and Michael Genkin. Besides the Paris and Brussels attacks, the network includes related operations such as the attack on the Jewish Museum of Belgium (May 2014), the interdicted plot in Verviers (January 2015), and the attack on the Brussels-Paris high-speed train (August 2015). The data were coded from large-circulation media sources (mostly French, Dutch and English-language newspapers, and the Lexis database), collected from November 17, 2015 to May 9, 2016, into a graph database of persons, attacks, covert or non-covert activities, sites (e.g. residences and safe houses), localities and countries, with relations such as a person involved in an attack or activity, linked to another person (kinship, affinity, operational work), or present in a site or locality. Persons were included if they were attackers, involved with an attacker in a terrorism-related task, or wanted or arrested in relation to the attacks. The social networks between persons were then inferred from the database. Nodes are persons, and undirected edges are inferred ties, obtained with three different rules for the sensitivity analysis of the authors:

  • network (IS-E): two persons are tied if they took part in an attack on the same site, were involved in the same activity, had a pre-existing link and one of them is an attacker or a wanted or dead member, or shared a site (e.g. a residence or safe house) and are both suspects, or one is an attacker.
  • restricted (IS-E restricted): as network, but without the ties based on shared sites.
  • extended (IS-E extended): as network, plus ties between suspects present in the same locality (e.g. the Molenbeek district of Brussels).

All networks contain the same nodes: all persons in the data whose status is not "free" (i.e. arrested, dead or wanted), plus one person with status "free" who has ties, as in the GML files of the authors. Persons without ties under a given rule are isolated nodes. One self-loop of the source data in the extended network (a person tied to themself by a shared locality) is removed. This is the latest version of the data, as of August 2017 (the ICON record refers to an earlier version of November 2015, with 24 nodes and 35 edges).

The networks have the following properties:

  • Nodes: name, the name of the person (sometimes only partially known, or a placeholder description); age, the age of the person (-1 if unknown); citizenship; status, "arrested", "dead", "wanted" or "free"; role, the role of the person, if known (e.g. "logistics", "commander", "bomb maker"); ref, the media source reporting on the person; attacker, whether the person was involved in an attack; involved_in_activity, whether the person was involved in an activity; linked_to_attacker, whether the person (a suspect) is linked to an attacker.
  • Edges: boolean flags for the grounds of each tie (several can apply): common_attack (involved in an attack on the same site), linked_to_attacker (pre-existing link of a suspect with an attacker), linked_to_each_other (any pre-existing link between the two persons; not used by itself as a ground for a tie), linked_to_wanted (pre-existing link of a suspect with a wanted or dead person), common_involvement (involved in the same activity), shared_site_with_attacker (a suspect present in the same site as an attacker), shared_site_with_suspect (two suspects related to the same site), shared_locality_with_suspect (two suspects present in the same locality).
Tags
Social Offline Unweighted Metadata
Citation
  • A. Gutfraind, M. Genkin, "A graph database framework for covert network analysis: An application to the Islamic State network in Europe." Social Networks 51, 178-188 (2017) 10.1016/j.socnet.2016.10.004 Sci-Hub
Upstream URL OK
https://github.com/sashagutfraind/Nov13
Upstream license
CC BY 4.0, https://github.com/sashagutfraind/Nov13/blob/bc1d58acee7e12b7cd106f1ec79f117a5807bfeb/LICENSE.md
Networks
Tip: click on a column header to sort the list, or hover over it for a description.
Column legend
$\left<k\right>$
Mean degree
$\sigma_k$
Standard deviation of the degrees
$\lambda_h$
Largest eigenvalue of the Hashimoto (non-backtracking) matrix
$\tau$
Random walk mixing time
$r$
Degree assortativity
$c$
Global clustering coefficient
$\oslash$
(Pseudo-) diameter
$S$
Relative size of the largest component
NPs
Node properties
EPs
Edge properties
Name Nodes Edges $\left<k\right>$ $\sigma_k$ $\lambda_h$ $\tau$ $r$ $c$ $\oslash$ $S$ Kind Mode NPs EPs gt GraphML GML csv
network 85 197 4.64 5.39 8.05 9.82 -0.20 0.32 6 0.91 Undirected Unipartite name age citizenship status role ref attacker involved_in_activity linked_to_attacker common_attack linked_to_attacker linked_to_each_other linked_to_wanted common_involvement shared_site_with_attacker shared_site_with_suspect shared_locality_with_suspect 7 KiB 9 KiB 9 KiB 8 KiB
restricted 85 163 3.84 4.92 7.50 10.94 -0.22 0.32 6 0.84 Undirected Unipartite name age citizenship status role ref attacker involved_in_activity linked_to_attacker common_attack linked_to_attacker linked_to_each_other linked_to_wanted common_involvement shared_site_with_attacker shared_site_with_suspect shared_locality_with_suspect 7 KiB 9 KiB 8 KiB 8 KiB
extended 85 273 6.42 6.78 12.50 9.34 -0.12 0.50 6 0.91 Undirected Unipartite name age citizenship status role ref attacker involved_in_activity linked_to_attacker common_attack linked_to_attacker linked_to_each_other linked_to_wanted common_involvement shared_site_with_attacker shared_site_with_suspect shared_locality_with_suspect 7 KiB 10 KiB 9 KiB 8 KiB
Ridiculograms*
* These are automatically generated force-directed visualizations, and can be quite meaningless for networks both big and small. They should not be taken seriously as sources of scientific insight. See here for a discussion.