MIDAS at SemEval-2019 Task 6: Identifying Offensive Posts and Targeted Offense from Twitter
Autor: | Sarthak Anand, Rajiv Ratn Shah, Haimin Zhang, Simra Shahid, Debanjan Mahata, Karan Uppal, Yaman Kumar, Laiba Mehnaz |
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Rok vydání: | 2019 |
Předmět: |
business.industry
Computer science Offensive 02 engineering and technology computer.software_genre Convolutional neural network SemEval Task (project management) 020204 information systems 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Artificial intelligence F1 score Set (psychology) Heuristics business computer Natural language processing |
Zdroj: | SemEval@NAACL-HLT |
Popis: | In this paper we present our approach and the system description for Sub Task A and Sub Task B of SemEval 2019 Task 6: Identifying and Categorizing Offensive Language in Social Media. Sub Task A involves identifying if a given tweet is offensive and Sub Task B involves detecting if an offensive tweet is targeted towards someone (group or an individual). Our models for Sub Task A is based on an ensemble of Convolutional Neural Network and Bidirectional LSTM, whereas for Sub Task B, we rely on a set of heuristics derived from the training data. We provide detailed analysis of the results obtained using the trained models. Our team ranked 5th out of 103 participants in Sub Task A, achieving a macro F1 score of 0.807, and ranked 8th out of 75 participants achieving a macro F1 of 0.695. |
Databáze: | OpenAIRE |
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