This study focuses on the outpouring of sympathy in response to mass shootings and the contestation over gun policy on Twitter from 2012 to 2014 and relates these discourses to features of mass shooting events. We use two approaches to Twitter text analysis—hashtag grouping and supervised machine learning (ML)—to triangulate an understanding of intensity and duration of “thoughts and prayers,” gun control, and gun rights discourses. We conduct parallel time series analyses to predict their temporal patterns in response to features of mass shootings. Our analyses reveal that while the total number of victims and child deaths consistently predicted public grieving and calls for gun control, public shootings consistently predicted the defense of gun rights. Further, the race of victims and perpetrators affected the levels of public mourning and policy debates, with the loss of black lives and the violence inflicted by white shooters generating less sympathy and policy discourses.

中文翻译：

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谁活着？2012-2014年的集体射击和同情与政策社交媒体话语

这项研究的重点是在2012年至2014年期间针对大规模枪击事件表达同情心，并在Twitter上对枪支政策提出质疑，并将这些论述与大规模枪击事件的特征联系起来。我们使用两种方法进行Twitter文本分析-标签分组和有监督的机器学习（ML）-对“思想和祈祷”的强度和持续时间，枪支控制和枪支权利话语的理解进行三角划分。我们进行并行的时间序列分析，以预测大规模射击事件的时间模式。我们的分析表明，虽然受害者和儿童死亡的总数始终预示着公众的悲痛和对枪支控制的呼吁，但公共枪击事件始终预示着捍卫枪支权利的行为。进一步，