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Correlations and forecast of death tolls in the Syrian conflict

Correlations and forecast of death tolls in the Syrian conflict

Fujita, Kazuki, Shinomoto, Shigeru and Rocha, Luis E. C. ORCID: 0000-0001-9046-8739 (2017) Correlations and forecast of death tolls in the Syrian conflict. Scientific Reports, 7 (1):15737. ISSN 2045-2322 (Online) (doi:10.1038/s41598-017-15945-x)

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Abstract

The Syrian armed conflict has been ongoing since 2011 and has already caused thousands of deaths. The analysis of death tolls helps to understand the dynamics of the conflict and to better allocate resources and aid to the affected areas. In this article, we use information on the daily number of deaths to study temporal and spatial correlations in the data, and exploit this information to forecast events of deaths. We found that the number of violent deaths per day in Syria varies more widely than that in England in which non-violent deaths dominate. We have identified strong positive auto-correlations in Syrian cities and non-trivial cross-correlations across some of them. The results indicate synchronization in the number of deaths at different times and locations, suggesting respectively that local attacks are followed by more attacks at subsequent days and that coordinated attacks may also take place across different locations. Thus the analysis of high temporal resolution data across multiple cities makes it possible to infer attack strategies, warn potential occurrence of future events, and hopefully avoid further deaths.

Item Type: Article
Additional Information: © The Author(s) 2017. Open Access. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
Uncontrolled Keywords: Time series analysis, Syria Conflict, Death tolls
Subjects: H Social Sciences > HA Statistics
Faculty / Department / Research Group: Faculty of Business
Faculty of Business > Centre for Business Network Analysis
Faculty of Business > Department of International Business & Economics
Last Modified: 09 May 2018 13:59
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: GREAT e
URI: http://gala.gre.ac.uk/id/eprint/19626

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