SemEval 2019 Task 6 - OffensEval: Identifying and Categorizing Offensive Language in Social Media Shared Task Website: https://competitions.codalab.org/competitions/20011
Offensive language is pervasive in social media. Online communities, social media platforms, and technology companies have been investing heavily in ways to cope with offensive language to prevent abusive behavior in social media. One of the most effective strategies for tackling this problem is to use computational methods to identify offense, aggression, and hate speech in user-generated content (e.g. posts, comments, microblogs, etc.).
In OffensEval we provide participants with a dataset containing posts from social media. The trial dataset is available.
In OffensEval we break down offensive content into three sub-tasks taking the type and target of offenses into account:
Sub-task A - Offensive language identification; Sub-task B - Automatic categorization of offense types; Sub-task C - Offense target identification.
10 Oct 2018: Training Data Release 10 Jan 2019 - 23 Jan 2019: Evaluation Phase 28 Jan 2019: Results announced 28 Feb 2019: System paper submissions due 06 Apr 2019: Author notifications 20 Apr 2019: Camera ready submissions due
The complete list of dates is available on the task website.
Marcos Zampieri (University of Wolverhampton, UK) Shervin Malmasi (Harvard Medical School, USA) Preslav Nakov (Qatar Computing Research Insitute, Qatar) Sara Rosenthal (IBM Research, USA) Noura Farra (Columbia University, USA) Ritesh Kumar (Bhim Rao Ambedkar University, India)
----- Dr. Marcos Zampieri Research Group in Computational Linguistics University of Wolverhampton, UK http://pers-www.wlv.ac.uk/~u22984/