HAD-Tübingen at SemEval-2019 Task 6: Deep Learning Analysis of Offensive Language on Twitter: Identification and Categorization
Himanshu Bansal, Daniel Nagel, А. В. Соловьева · 2019
This paper describes the submissions of our team, HAD-Tübingen, 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 F 1 scores obtained for the sub-tasks A, B and C are 0.73, 0.52, and 0.37, respectively.