Detection of abusive messages in an on-line community

Etienne Papegnies, Vincent Labatut, Richard Dufour, G. Linarès
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引用次数: 15

Abstract

Moderating user content in online communities is mainly performed manually, and reducing the workload through automatic methods is of great interest. The industry mainly uses basic approaches such as bad words filtering. In this article, we consider the task of automatically determining whether a message is abusive or not. This task is complex, because messages are written in a non-standardized natural language. We propose an original automatic moderation method applied to French, which is based on both traditional tools and a newly proposed context-based feature relying on the modeling of user behavior when reacting to a message. The results obtained during this preliminary study show the potential of the proposed method, in a context of automatic processing or decision support.
在线社区中滥用信息的检测
在线社区中的用户内容审核主要是手动完成的,通过自动方法减少工作量是一个非常有趣的问题。该行业主要使用一些基本的方法,比如过滤坏词。在本文中,我们考虑自动确定消息是否为滥用的任务。这个任务很复杂,因为消息是用非标准化的自然语言编写的。我们提出了一种适用于法语的原创自动审核方法,该方法基于传统工具和新提出的基于上下文的功能,该功能依赖于用户对消息做出反应时的行为建模。在这项初步研究中获得的结果显示了所提出的方法在自动处理或决策支持方面的潜力。
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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