HAD-T\"ubingen at SemEval-2019 Task 6: Deep Learning Analysis of Offensive Language on Twitter: Identification and Categorization

Abstract

This paper describes the submissions of our team, HAD-T\"ubingen, for the SemEval 2019 - Task 6: ``OffensEval: Identifying and Categorizing Offensive Language in Social Media''. We participated in all the three sub-tasks: Sub-task A - ``Offensive language identification'', sub-task B - ``Automatic categorization of offense types'' and sub-task C - ``Offense target identification''. As a baseline model we used a Long short-term memory recurrent neural network (LSTM) to identify and categorize offensive tweets. For all the tasks we experimented with external databases in a postprocessing step to enhance the results made by our model. The best macro-average F1 scores obtained for the sub-tasks A, B and C are 0.73, 0.52, and 0.37, respectively.

Tasks

Reproductions