Binarizer at SemEval-2018 Task 3: Parsing dependency and deep learning for irony detection

May 03, 2018 ยท Declared Dead ยท ๐Ÿ› International Workshop on Semantic Evaluation

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Authors Nishant Nikhil, Muktabh Mayank Srivastava arXiv ID 1805.01112 Category cs.CL: Computation & Language Citations 5 Venue International Workshop on Semantic Evaluation Last Checked 5 months ago
Abstract
In this paper, we describe the system submitted for the SemEval 2018 Task 3 (Irony detection in English tweets) Subtask A by the team Binarizer. Irony detection is a key task for many natural language processing works. Our method treats ironical tweets to consist of smaller parts containing different emotions. We break down tweets into separate phrases using a dependency parser. We then embed those phrases using an LSTM-based neural network model which is pre-trained to predict emoticons for tweets. Finally, we train a fully-connected network to achieve classification.
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