Zewen at SemEval-2018 Task 1: An Ensemble Model for Affect Prediction in Tweets

Zewen Chi, Heyan Huang, Jiangui Chen, Hao Wu, Ran Wei

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

This paper presents a method for Affect in Tweets, which is the task to automatically determine the intensity of emotions and intensity of sentiment of tweets. The term affect refers to emotion-related categories such as anger, fear, etc. Intensity of emotions need to be quantified into a real valued score in [0, 1]. We propose an ensemble system including four different deep learning methods which are CNN, Bidirectional LSTM (BLSTM), LSTM-CNN and a CNN-based Attention model (CA). Our system gets an average Pearson correlation score of 0.682 in the subtask EI-reg and an average Pearson correlation score of 0.784 in subtask V-reg, which ranks 19th among 48 systems in EI-reg and 17th among 38 systems in V-reg.

源语言英语
主期刊名NAACL HLT 2018 - International Workshop on Semantic Evaluation, SemEval 2018 - Proceedings of the 12th Workshop
编辑Marianna Apidianaki, Marianna Apidianaki, Saif M. Mohammad, Jonathan May, Ekaterina Shutova, Steven Bethard, Marine Carpuat
出版商Association for Computational Linguistics (ACL)
313-318
页数6
ISBN(电子版)9781948087209
出版状态已出版 - 2018
活动12th International Workshop on Semantic Evaluation, SemEval 2018, co-located with the 16th Annual Conference of the North American Chapter of the - New Orleans, 美国
期限: 5 6月 20186 6月 2018

出版系列

姓名NAACL HLT 2018 - International Workshop on Semantic Evaluation, SemEval 2018 - Proceedings of the 12th Workshop

会议

会议12th International Workshop on Semantic Evaluation, SemEval 2018, co-located with the 16th Annual Conference of the North American Chapter of the
国家/地区美国
New Orleans
时期5/06/186/06/18

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