Abstract
Recent studies examine factors that lead to the emergence of terrorism and why some locations are more frequently targeted than others. However, much of the research assumes that terrorist incidents and groups are independent. We show that the assumption of independence is not always valid. Instead, we identify the conditions under which terrorist groups share choices over target locations, forming Implicit Terrorist Networks. We demonstrate the utility of this approach by examining Islamic terrorism in India (1990–2015). Using a two-mode network approach, we find that violent target locations are not independent of each other, but instead have a tendency to occur in clusters. The results highlight the patterns by which India has been targeted by a number of active, Islamic terrorist organizations over a 25-year period. More generally, our study: (1) demonstrates the utility of employing an Implicit Network approach to understanding terrorism, (2) shows that cluster analysis can assist in identifying terror group aliases, (3) identifies unexpected locations for violence that may indicate the involvement of external factors, providing leads for counter terrorism efforts, and (4) provides a tool for identifying the structures underlying patterns of global terrorism.
| Original language | English (US) |
|---|---|
| Title of host publication | Social, Cultural, and Behavioral Modeling - 11th International Conference, SBP-BRiMS 2018, Proceedings |
| Editors | Halil Bisgin, Robert Thomson, Ayaz Hyder, Christopher Dancy |
| Publisher | Springer Verlag |
| Pages | 340-347 |
| Number of pages | 8 |
| ISBN (Print) | 9783319933719 |
| DOIs | |
| State | Published - Jan 1 2018 |
| Event | 11th International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction conference and Behavior Representation in Modeling and Simulation, SBP-BRiMS 2018 - Washington, United States Duration: Jul 10 2018 → Jul 13 2018 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 10899 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Other
| Other | 11th International Conference on Social Computing, Behavioral-Cultural Modeling, and Prediction conference and Behavior Representation in Modeling and Simulation, SBP-BRiMS 2018 |
|---|---|
| Country | United States |
| City | Washington |
| Period | 7/10/18 → 7/13/18 |
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All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Computer Science(all)
Cite this
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Implicit terrorist networks : A two-mode social network analysis of terrorism in India. / Yarlagadda, Rithvik; Felmlee, Diane Helen; Verma, Dinesh; Gartner, Scott Sigmund.
Social, Cultural, and Behavioral Modeling - 11th International Conference, SBP-BRiMS 2018, Proceedings. ed. / Halil Bisgin; Robert Thomson; Ayaz Hyder; Christopher Dancy. Springer Verlag, 2018. p. 340-347 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 10899 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - Implicit terrorist networks
T2 - A two-mode social network analysis of terrorism in India
AU - Yarlagadda, Rithvik
AU - Felmlee, Diane Helen
AU - Verma, Dinesh
AU - Gartner, Scott Sigmund
PY - 2018/1/1
Y1 - 2018/1/1
N2 - Recent studies examine factors that lead to the emergence of terrorism and why some locations are more frequently targeted than others. However, much of the research assumes that terrorist incidents and groups are independent. We show that the assumption of independence is not always valid. Instead, we identify the conditions under which terrorist groups share choices over target locations, forming Implicit Terrorist Networks. We demonstrate the utility of this approach by examining Islamic terrorism in India (1990–2015). Using a two-mode network approach, we find that violent target locations are not independent of each other, but instead have a tendency to occur in clusters. The results highlight the patterns by which India has been targeted by a number of active, Islamic terrorist organizations over a 25-year period. More generally, our study: (1) demonstrates the utility of employing an Implicit Network approach to understanding terrorism, (2) shows that cluster analysis can assist in identifying terror group aliases, (3) identifies unexpected locations for violence that may indicate the involvement of external factors, providing leads for counter terrorism efforts, and (4) provides a tool for identifying the structures underlying patterns of global terrorism.
AB - Recent studies examine factors that lead to the emergence of terrorism and why some locations are more frequently targeted than others. However, much of the research assumes that terrorist incidents and groups are independent. We show that the assumption of independence is not always valid. Instead, we identify the conditions under which terrorist groups share choices over target locations, forming Implicit Terrorist Networks. We demonstrate the utility of this approach by examining Islamic terrorism in India (1990–2015). Using a two-mode network approach, we find that violent target locations are not independent of each other, but instead have a tendency to occur in clusters. The results highlight the patterns by which India has been targeted by a number of active, Islamic terrorist organizations over a 25-year period. More generally, our study: (1) demonstrates the utility of employing an Implicit Network approach to understanding terrorism, (2) shows that cluster analysis can assist in identifying terror group aliases, (3) identifies unexpected locations for violence that may indicate the involvement of external factors, providing leads for counter terrorism efforts, and (4) provides a tool for identifying the structures underlying patterns of global terrorism.
UR - http://www.scopus.com/inward/record.url?scp=85049798171&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85049798171&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-93372-6_37
DO - 10.1007/978-3-319-93372-6_37
M3 - Conference contribution
AN - SCOPUS:85049798171
SN - 9783319933719
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 340
EP - 347
BT - Social, Cultural, and Behavioral Modeling - 11th International Conference, SBP-BRiMS 2018, Proceedings
A2 - Bisgin, Halil
A2 - Thomson, Robert
A2 - Hyder, Ayaz
A2 - Dancy, Christopher
PB - Springer Verlag
ER -