Abstract
Modeling behavior related to radicalization and terrorism is extremely complex. Consequently, the development of computational approaches to support an understanding of behavioral underpinnings that lead up to radicalization is a significant undertaking and necessitates either a decomposition of behavioral activity into smaller, more manageable behaviors or generalizing larger, group behavior so that only gross trends may be observed. While these approaches may suffice for particular applications, additional consideration should be given to developing more comprehensive or whole-system modeling approaches so as to inform decision-makers in making complex judgments. Specifically for those seeking to understand and stop terrorism, a number of social, cultural, and behavioral perspectives are being developed by experts worldwide. Our research seeks to develop computational methods to analyze and experiment with differing views, opinions, and perspectives of potential influences on adversarial behavior by providing the capability to 'dock' or integrate models. We demonstrate how this ability allows for a multi-scale comprehension of the factors that contribute to radicalization.
| Original language | English (US) |
|---|---|
| Title of host publication | IEEE ISI 2013 - 2013 IEEE International Conference on Intelligence and Security Informatics |
| Subtitle of host publication | Big Data, Emergent Threats, and Decision-Making in Security Informatics |
| Pages | 251-253 |
| Number of pages | 3 |
| DOIs | |
| State | Published - Sep 9 2013 |
| Event | 11th IEEE International Conference on Intelligence and Security Informatics, IEEE ISI 2013 - Seattle, WA, United States Duration: Jun 4 2013 → Jun 7 2013 |
Publication series
| Name | IEEE ISI 2013 - 2013 IEEE International Conference on Intelligence and Security Informatics: Big Data, Emergent Threats, and Decision-Making in Security Informatics |
|---|
Other
| Other | 11th IEEE International Conference on Intelligence and Security Informatics, IEEE ISI 2013 |
|---|---|
| Country | United States |
| City | Seattle, WA |
| Period | 6/4/13 → 6/7/13 |
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All Science Journal Classification (ASJC) codes
- Artificial Intelligence
- Information Systems
Cite this
}
A model docking system for understanding radicalization. / Weiss, Lora G.; Briscoe, Erica; Wright, Walter; Harbert, Sim; Kline, Keith; Horgan, John; Cushenbery, Lily; Hilland, Casey.
IEEE ISI 2013 - 2013 IEEE International Conference on Intelligence and Security Informatics: Big Data, Emergent Threats, and Decision-Making in Security Informatics. 2013. p. 251-253 6578829 (IEEE ISI 2013 - 2013 IEEE International Conference on Intelligence and Security Informatics: Big Data, Emergent Threats, and Decision-Making in Security Informatics).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
TY - GEN
T1 - A model docking system for understanding radicalization
AU - Weiss, Lora G.
AU - Briscoe, Erica
AU - Wright, Walter
AU - Harbert, Sim
AU - Kline, Keith
AU - Horgan, John
AU - Cushenbery, Lily
AU - Hilland, Casey
PY - 2013/9/9
Y1 - 2013/9/9
N2 - Modeling behavior related to radicalization and terrorism is extremely complex. Consequently, the development of computational approaches to support an understanding of behavioral underpinnings that lead up to radicalization is a significant undertaking and necessitates either a decomposition of behavioral activity into smaller, more manageable behaviors or generalizing larger, group behavior so that only gross trends may be observed. While these approaches may suffice for particular applications, additional consideration should be given to developing more comprehensive or whole-system modeling approaches so as to inform decision-makers in making complex judgments. Specifically for those seeking to understand and stop terrorism, a number of social, cultural, and behavioral perspectives are being developed by experts worldwide. Our research seeks to develop computational methods to analyze and experiment with differing views, opinions, and perspectives of potential influences on adversarial behavior by providing the capability to 'dock' or integrate models. We demonstrate how this ability allows for a multi-scale comprehension of the factors that contribute to radicalization.
AB - Modeling behavior related to radicalization and terrorism is extremely complex. Consequently, the development of computational approaches to support an understanding of behavioral underpinnings that lead up to radicalization is a significant undertaking and necessitates either a decomposition of behavioral activity into smaller, more manageable behaviors or generalizing larger, group behavior so that only gross trends may be observed. While these approaches may suffice for particular applications, additional consideration should be given to developing more comprehensive or whole-system modeling approaches so as to inform decision-makers in making complex judgments. Specifically for those seeking to understand and stop terrorism, a number of social, cultural, and behavioral perspectives are being developed by experts worldwide. Our research seeks to develop computational methods to analyze and experiment with differing views, opinions, and perspectives of potential influences on adversarial behavior by providing the capability to 'dock' or integrate models. We demonstrate how this ability allows for a multi-scale comprehension of the factors that contribute to radicalization.
UR - http://www.scopus.com/inward/record.url?scp=84883429618&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84883429618&partnerID=8YFLogxK
U2 - 10.1109/ISI.2013.6578829
DO - 10.1109/ISI.2013.6578829
M3 - Conference contribution
AN - SCOPUS:84883429618
SN - 9781467362115
T3 - IEEE ISI 2013 - 2013 IEEE International Conference on Intelligence and Security Informatics: Big Data, Emergent Threats, and Decision-Making in Security Informatics
SP - 251
EP - 253
BT - IEEE ISI 2013 - 2013 IEEE International Conference on Intelligence and Security Informatics
ER -