论文标题
复仇主题：在文本数据中自动识别复仇内容
Themes of Revenge: Automatic Identification of Vengeful Content in Textual Data
论文作者
论文摘要
复仇是一支强大的激励力量，据报道是从学校射击者到右翼恐怖分子的各种肇事者的行为的基础。在本文中，我们开发了一种自动化方法，用于识别文本数据中的复仇主题。在四个数据集上测试该模型（社交媒体，学校射击者，右翼恐怖分子和伊斯兰恐怖分子的复仇文本），即使在极度不平衡的数据集中测试了方法，我们也会提出令人鼓舞的结果。本文不仅提出了一种简单而有力的方法，可用于筛选独奏肇事者，而且还验证了简单的复仇理论模型。
Revenge is a powerful motivating force reported to underlie the behavior of various solo perpetrators, from school shooters to right wing terrorists. In this paper, we develop an automated methodology for identifying vengeful themes in textual data. Testing the model on four datasets (vengeful texts from social media, school shooters, Right Wing terrorist and Islamic terrorists), we present promising results, even when the methodology is tested on extremely imbalanced datasets. The paper not only presents a simple and powerful methodology that may be used for the screening of solo perpetrators but also validate the simple theoretical model of revenge.
