Predicting non-state terrorism worldwide-Reference-Cited by-同舟云学术

Predicting non-state terrorism worldwide

Published:2021-07-30 Issue:31 Volume:7 Page:
ISSN:2375-2548
Container-title:Science Advances
language:en
Short-container-title:Sci. Adv.

Author:

Python Andre¹²^ORCID,Bender Andreas³^ORCID,Nandi Anita K.²^ORCID,Hancock Penelope A.²^ORCID,Arambepola Rohan²,Brandsch Jürgen⁴^ORCID,Lucas Tim C. D.⁵^ORCID

Affiliation:

1. Center for Data Science, Zhejiang University, Hangzhou, P.R. China.

2. Li Ka Shing Centre for Health Information and Discovery, Oxford University, Nuffield Department of Medicine, Big Data Institute, Oxford, UK.

3. Department of Statistics, LMU Munich, Munich, Germany.

4. Bonn International Center for Conversion (BICC), Bonn, Germany.

5. School of Public Health, Imperial College London, London, UK.

Abstract

Predictive models informed by theory may produce policy-relevant prediction of terrorism.

Funder

Zhejiang University

German Federal Ministry of Education and Research

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

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