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SemEval-2019 Task 6: Identifying and Categorizing Offensive Language in Social Media (OffensEval)

机译:SemEval-2019任务6:在社交媒体中识别和分类攻击性语言(OffensEval)

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We present the results and the main findings of SemEval-2019 Task 6 on Identifying and Categorizing Offensive Language in Social Media (OffensEval). The task was based on a new dataset, the Offensive Language Identification Dataset (OLID), which contains over 14,000 English tweets. It featured three sub-tasks. In sub-task A, the goal was to discriminate between offensive and non-offensive posts. In sub-task B, the focus was on the type of offensive content in the post. Finally, in sub-task C, systems had to detect the target of the offensive posts. OffensEval attracted a large number of participants and it was one of the most popular tasks in SemEval-2019. In total, about 800 teams signed up to participate in the task, and 115 of them submitted results, which we present and analyze in this report.
机译:我们介绍了SemEval-2019任务6有关在社交媒体中识别和分类攻击性语言(OffensEval)的结果和主要发现。该任务基于一个新的数据集,即冒犯性语言识别数据集(OLID),其中包含14,000多个英语推文。它具有三个子任务。在子任务A中,目标是区分进攻性和非进攻性职位。在子任务B中,重点是帖子中令人反感的内容的类型。最后,在子任务C中,系统必须检测进攻目标的目标。 OffensEval吸引了大量参与者,这是SemEval-2019中最受欢迎的任务之一。总共约有800个团队报名参加了该任务,其中115个团队提交了结果,我们在本报告中进行了分析。

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