Publication | Open Access
SemEval-2019 Task 6: Identifying and Categorizing Offensive Language in Social Media (OffensEval)
673
Citations
41
References
2019
Year
Unknown Venue
Abuse DetectionEngineeringSocial Medium MonitoringCommunicationCorpus LinguisticsSemeval-2019 Task 6Text MiningNatural Language ProcessingComputational Social ScienceSocial MediaLanguage StudiesContent AnalysisSocial Medium MiningEnglish TweetsCategorizing Offensive LanguageLanguage PolicingSocial ComputingSocial Medium DataLinguistics
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.
| Year | Citations | |
|---|---|---|
Page 1
Page 1