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arxiv: 1903.08983 · v3 · pith:MBSRRJHHnew · submitted 2019-03-19 · 💻 cs.CL

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

Marcos Zampieri , Shervin Malmasi , Preslav Nakov , Sara Rosenthal , Noura Farra , Ritesh Kumar This is my paper
classification 💻 cs.CL
keywords offensivetasklanguageoffensevalsemeval-2019sub-taskcategorizingdataset
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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.

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