UM-IU@LING at SemEval-2019 Task 6: Identifying Offensive Tweets Using BERT and SVMs
Jian Ying Zhu, Zuoyu Tian, Sandra Kübler · 2019
This paper describes the UM-IU@LING's system for the SemEval 2019 Task 6: OffensEval.We take a mixed approach to identify and categorize hate speech in social media.In subtask A, we fine-tuned a BERT based classifier to detect abusive content in tweets, achieving a macro F 1 score of 0.8136 on the test data, thus reaching the 3rd rank out of 103 submissions.In subtasks B and C, we used a linear SVM with selected character n-gram features.For subtask C, our system could identify the target of abuse with a macro F 1 score of 0.5243, ranking it 27th out of 65 submissions.