Correlations and forecast of death tolls in the Syrian conflict.
Correlations and forecast of death tolls in the Syrian conflict.
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DOI：
10.1038/s41598-017-15945-x
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发表时间：
2017-11-16
影响因子：
4.6
通讯作者：
Rocha LEC
中科院分区：
文献类型：
--
作者：
Fujita K;Shinomoto S;Rocha LEC
叙利亚武装冲突自2011年以来一直持续，已经造成数千人死亡。对死亡人数的分析有助于了解冲突的动态，并更好地向受影响地区分配资源和援助。在这篇文章中，我们使用每日死亡人数的信息来研究数据中的时间和空间相关性，并利用这些信息来预测死亡事件。我们发现，叙利亚每天的暴力死亡人数比非暴力死亡占主导地位的英国差异更大。我们已经确定了叙利亚城市的强正自相关性和其中一些城市的非平凡互相关性。这些结果表明，不同时间和地点的死亡人数是同步的，分别表明当地袭击之后是随后几天的更多袭击，协调袭击也可能发生在不同地点。因此，对多个城市的高时间分辨率数据进行分析，可以推断攻击策略，警告未来事件的潜在发生，并希望避免更多的死亡。
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.
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