ConvAI at SemEval-2019 Task 6: Offensive Language Identification and Categorization with Perspective and BERT
This paper presents the application of two strong baseline systems for toxicity detection and evaluates their performance in identifying and categorizing offensive language in social media. PERSPECTIVE is an API, that serves multiple machine learning models for the improvement of conversations online, as well as a toxicity detection system, trained on a wide variety of comments from platforms across the Internet. BERT is a recently popular language representation model, fine tuned per task and achieving state of the art performance in multiple NLP tasks. PERSPECTIVE performed better than BERT in detecting toxicity, but BERT was much better in categorizing the offensive type. Both baselines were ranked surprisingly high in the SEMEVAL-2019 OFFENSEVAL competition, PERSPECTIVE in detecting an offensive post (12th) and BERT in categorizing it (11th). The main contribution of this paper is the assessment of two strong baselines for the identification (PERSPECTIVE) and the categorization (BERT) of offensive language with little or no additional training data.
Code (0)
등록된 구현이 없습니다.
Tasks
Language IdentificationMethods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
Hitachi at SemEval-2020 Task 12: Offensive Language Identification with Noisy Labels using Statistical Sampling and Post-Processing
In this paper, we present our participation in SemEval-2020 Task-12 Subtask-A (English Language) which focuses on offensive language identification from noisy labels. To this end, we developed a hybrid system with the BE…
Language IdentificationPositionLaSTUS/TALN at SemEval-2019 Task 6: Identification and Categorization of Offensive Language in Social Media with Attention-based Bi-LSTM model
We present a bidirectional Long-Short Term Memory network for identifying offensive language in Twitter. Our system has been developed in the context of the SemEval 2019 Task 6 which comprises three different sub-tasks, …
Word EmbeddingsGalileo at SemEval-2020 Task 12: Multi-lingual Learning for Offensive Language Identification using Pre-trained Language Models
This paper describes Galileo's performance in SemEval-2020 Task 12 on detecting and categorizing offensive language in social media. For Offensive Language Identification, we proposed a multi-lingual method using Pre-tra…
AllKnowledge DistillationLanguage IdentificationXLM-RDeepAnalyzer at SemEval-2019 Task 6: A deep learning-based ensemble method for identifying offensive tweets
This paper describes the system we developed for SemEval 2019 on Identifying and Categorizing Offensive Language in Social Media (OffensEval - Task 6). The task focuses on offensive language in tweets. It is organized in…
Language IdentificationPart-Of-Speech TaggingKS@LTH at SemEval-2020 Task 12: Fine-tuning Multi- and Monolingual Transformer Models for Offensive Language Detection
This paper describes the KS@LTH system for SemEval-2020 Task 12 OffensEval2: Multilingual Offensive Language Identification in Social Media. We compare mono- and multilingual models based on fine-tuning pre-trained trans…
Language Identification