Big Data, Selection Bias, and the Statistical Patterns of Mortality in Conflict
Big Data, Selection Bias, and the Statistical Patterns of Mortality in Conflict
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大数据、选择偏差和冲突中死亡率的统计模式
DOI：
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发表时间：
2014
期刊：
影响因子：
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通讯作者：
P. Ball
中科院分区：
文献类型：
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作者：
Megan Price;P. Ball
“大数据”的概念意味着非常具体的技术假设。使大数据在私营部门变得非常强大的工具取决于拥有所有（或几乎所有）可能的数据。根据我们的经验，这些技术假设很少与有关政策和社会世界的数据相吻合。本文探讨了冲突中杀戮的信息是如何产生的，以及信息产生的过程如何塑造观察到的数据中的统计模式。使用来自叙利亚和伊拉克的案例研究，我们强调了观察到的数据中的偏见可能误导政策的方式。本文件最后提出了关于在制定政策时使用数据和分析的建议。
The notion of “big data” implies very specific technical assumptions. The tools that have made big data immensely powerful in the private sector depend on having all (or nearly all) of the possible data. In our experience, these technical assumptions are rarely met with data about the policy and social world. This paper explores how information is generated about killings in conflict, and how the process of information generation shapes the statistical patterns in the observed data. Using case studies from Syria and Iraq, we highlight the ways in which bias in the observed data could mislead policy. The paper closes with recommendations about the use of data and analysis in the development of policy.