面向行为者的仇恨语音自动检测框架

Rinda Cahyana, N. Maulidevi, K. Surendro
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引用次数: 0

摘要

自动仇恨言论检测研究的发展尚未详细说明谁是仇恨的来源,尽管仇恨言论干预的形式对肇事者和支持者是不同的。以往对这一主题的研究主要关注情感词的行为成分。然而,尚未注意到演员成分,该成分可以区分合法的仇恨言论和非法的仇恨言论,并将仇恨或攻击性言论转化为自由言论,从而处理错误分类,如先前的研究所述。本研究提出了一个仇恨言论自动检测的框架,该框架提供了一个行动者和行动组件来解决此类错误问题,并满足综合干预的需要。本研究展示了如何在基于规则的方法中应用该框架,通过考虑演员成分来预测仇恨言论并将其与其他言论区分开来。这种预测过程被称为面向参与者的自动仇恨言论检测。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Framework for Actor-Oriented Automated Hate Speech Detection
The development of automated hate speech detection research has not yet detailed the actor who is the source of hatred, even though the forms of hate speech intervention for perpetrators and supporters are different. Previous research on this topic has paid much attention to the action component in the form of sentimental words. However, it has yet to pay attention to the actor component that can differentiate legal hate speech from illegal hate speech and transforms hateful or offensive speech into free speech, thus dealing with misclassification, as reported in a previous study. This research proposes a framework for the automated detection of hate speech that provides an actor and action component to solve the problem of such errors and meets the need for comprehensive interventions. This study shows how to apply the framework in a rule-based approach by considering the actor component in predicting hate speech and differentiating it from others. The prediction process is called actor-oriented automated hate speech detection.
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