Recognizing Emotion Cause in Conversations

• URL: http://arxiv.org/abs/2012.11820v2
• Date: Thu, 24 Dec 2020 08:43:38 GMT
• Title: Recognizing Emotion Cause in Conversations
• Authors: Soujanya Poria, Navonil Majumder, Devamanyu Hazarika, Deepanway Ghosal, Rishabh Bhardwaj, Samson Yu Bai Jian, Romila Ghosh, Niyati Chhaya, Alexander Gelbukh, Rada Mihalcea
• Abstract summary: Recognizing the cause behind emotions in text is a fundamental yet under-explored area of research in NLP. We introduce the task of recognizing emotion cause in conversations with an accompanying dataset named RECCON.
• Score: 82.88647116730691
• License: http://creativecommons.org/licenses/by-sa/4.0/
• Abstract: Recognizing the cause behind emotions in text is a fundamental yet under-explored area of research in NLP. Advances in this area hold the potential to improve interpretability and performance in affect-based models. Identifying emotion causes at the utterance level in conversations is particularly challenging due to the intermingling dynamic among the interlocutors. To this end, we introduce the task of recognizing emotion cause in conversations with an accompanying dataset named RECCON. Furthermore, we define different cause types based on the source of the causes and establish strong transformer-based baselines to address two different sub-tasks of RECCON: 1) Causal Span Extraction and 2) Causal Emotion Entailment. The dataset is available at https://github.com/declare-lab/RECCON.

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