How State and Protester Violence Affect Protest Dynamics
How State and Protester Violence Affect Protest Dynamics
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DOI：
10.1086/715600
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发表时间：
2021-05
期刊：
影响因子：
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通讯作者：
Zachary C. Steinert-Threlkeld;Alexander Chan;Jungseock Joo
中科院分区：
文献类型：
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作者：
Zachary C. Steinert-Threlkeld;Alexander Chan;Jungseock Joo
国家和抗议者的暴力如何影响抗议活动的增长或缩小？先前的研究发现暴力如何影响抗议动态的结果相互矛盾。本文认为，期望和情绪应该在国家镇压的严重程度和第二天抗议规模的变化之间产生n形关系。抗议者的暴力行为会降低抗议活动的吸引力，增加抗议活动的预期成本，减少随后的抗议规模。由于测试这一论点需要精确的测量，因此构建了一个管道，将卷积神经网络应用于地理定位推文中共享的图像。在五个国家的24个城市中，每个城市每天都会产生对国家和抗议者暴力行为的持续估值，以及对抗议规模和抗议者年龄和性别的估计。这些结果为镇压-异议之谜提供了一个解决方案，并加入了越来越多的研究机构，这些研究受益于使用社交媒体来了解国家以下各级的冲突。
How do state and protester violence affect whether protests grow or shrink? Previous research finds conflicting results for how violence affects protest dynamics. This article argues that expectations and emotions should generate an n-shaped relationship between the severity of state repression and changes in protest size the next day. Protester violence should reduce the appeal of protesting and increase the expected cost of protesting, decreasing subsequent protest size. Since testing this argument requires precise measurements, a pipeline is built that applies convolutional neural networks to images shared in geolocated tweets. Continuously valued estimates of state and protester violence are generated per city-day for 24 cities across five countries, as are estimates of protest size and the age and gender of protesters. The results suggest a solution to the repression-dissent puzzle and join a growing body of research benefiting from the use of social media to understand subnational conflict.