J 2018

Bayesian Geographical Profiling in Terrorism Revealing

SVOBODOVÁ, Jana and Jan KOLÁČEK

Basic information

Original name

Bayesian Geographical Profiling in Terrorism Revealing

Authors

SVOBODOVÁ, Jana (203 Czech Republic, guarantor, belonging to the institution) and Jan KOLÁČEK (203 Czech Republic, belonging to the institution)

Edition

STATISTIKA-STATISTICS AND ECONOMY JOURNAL, Czech Statistical Office, 2018, 0322-788X

Other information

Language

English

Type of outcome

Článek v odborném periodiku

Field of Study

10103 Statistics and probability

Country of publisher

Czech Republic

Confidentiality degree

není předmětem státního či obchodního tajemství

References:

RIV identification code

RIV/00216224:14310/18:00103782

Organization unit

Faculty of Science

UT WoS

000445278600006

Keywords in English

Bayesian data analysis; geographic profiling; Global Terrorism Database; anchor point

Tags

International impact, Reviewed
Změněno: 7/1/2019 10:19, doc. Mgr. Jan Koláček, Ph.D.

Abstract

V originále

A significant part of research in terrorism studies focuses on the analysis of terrorist groups. An important issue for this type of research is that a large number of attacks are not attributed to a specific group. As an appropriate approach to solve the problem of attributing group responsibility we applied the geographic profiling theory. We analyzed several terrorist organizations which typically commit attacks far away from their headquarters. We proposed an innovative method based on Bayesian approach to find the organization’s base and to attribute responsibility to perpetrators of terrorist attacks. We compared the results with classical techniques used in criminology. The real data analysis shows rationale for the proposed approach. Analyzed data comes from the Global Terrorism Database which is currently the most extensive database on terrorism ever collected.

Links

MUNI/A/1204/2017, interní kód MU
Name: Matematické statistické modelování 2 (Acronym: MaStaMo2)
Investor: Masaryk University, Category A