Predicting Targeted Violence from Social Media Communication

Lisa Kaati, A. Shrestha, N. Akrami
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Abstract

For decades, threat assessment professionals have used structured professional judgment instruments to make decisions about, for example, the likelihood of violent behavior of an individual. However, with the increased use of social media, most people use online digital platforms to communicate, which is also the case for potential violent offenders. For example, many mass shootings in recent years have been preceded by communication in online forums. In this paper, we introduce methods to identify markers of the warning behaviors Leakage, Fixation, Identification, and Affiliation and examine their discriminant validity. Our results show that violent offenders score higher on these markers and that these markers were present among a significantly higher proportion of violent offenders as compared to the normal population. We argue that our method can be used to predict potential planned, purposeful, or instrumental targeted violence in written communication. Automated methods for detecting warning behavior from written communication can serve as a complement to traditional threat assessment and provides unique opportunities for threat assessment beyond traditional methods.
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从社交媒体传播预测针对性暴力
几十年来,威胁评估专业人员一直使用结构化的专业判断工具来做出决定,例如,个人暴力行为的可能性。然而,随着社交媒体使用的增加,大多数人使用在线数字平台进行交流,潜在的暴力罪犯也是如此。例如,近年来的许多大规模枪击事件都是在网络论坛上进行交流的。本文介绍了预警行为“泄漏”、“固定”、“识别”和“隶属”标记的识别方法,并检验了它们的判别效度。我们的研究结果表明,暴力犯罪者在这些标记上得分更高,而且与正常人群相比,这些标记在暴力犯罪者中所占的比例要高得多。我们认为,我们的方法可以用来预测书面交流中潜在的有计划的、有目的的或工具性的有针对性的暴力。从书面通信中检测警告行为的自动化方法可以作为传统威胁评估的补充,并为超越传统方法的威胁评估提供独特的机会。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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