SemEval-2019 Task 6: Identifying and Categorizing Offensive Language in Social Media (OffensEval)
Citations Over TimeTop 1% of 2019 papers
Abstract
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.
Related Papers
- → SemEval-2007 task 07(2007)155 cited
- → IITP at SemEval-2017 Task 8 : A Supervised Approach for Rumour Evaluation(2017)26 cited
- → SemEval 2022 Task 12: Symlink - Linking Mathematical Symbols to their Descriptions(2022)15 cited
- → Cost-Sensitive Learning and Ensemble BERT for Identifying and Categorizing Offensive Language in Social Media(2021)3 cited
- → “Why do I feel offended?” - Korean Dataset for Offensive Language Identification(2023)3 cited