Emotions Relationship Modeling in the Conversation-Level Sentiment Analysis

Jieying Xue, Minh-Phuong Nguyen, Le-Minh Nguyen

2023

Abstract

Sentiment analysis, also called opinion mining, is a task of Natural Language Processing (NLP) that aims to extract sentiments and opinions from texts. Among them, emotion recognition in conversation (ERC) is becoming increasingly popular as a new research topic in natural language processing (NLP). The current state-of-the-art models focus on injecting prior knowledge via an external commonsense extractor or applying pre-trained language models to construct the utterance vector representation that is fused with the surrounding context in a conversation. However, these architectures treat the emotional states as sequential inputs, thus omitting the strong relationship between emotional states of discontinuous utterances, especially in long conversations. To solve this problem, we propose a new architecture, Long-range dependencY emotionS Model (LYSM) to generalize the dependencies between emotional states using the self-attention mechanism, which reinforces the emotion vector representations in the conversational encoder. Our intuition is that the emotional states in a conversation can be influenced or transferred across speakers and sentences, independent of the length of the conversation. Our experimental results show that our proposed architecture improves the baseline model and achieves competitive performance with state-of-the-art methods on four well-known benchmark datasets in this domain: IEMOCAP, DailyDialog, Emory NLP, and MELD. Our code is available at https://github.com/phuongnm94/erc-sentiment.

Paper Citation

in Harvard Style

Xue J., Nguyen M. and Nguyen L. (2023). Emotions Relationship Modeling in the Conversation-Level Sentiment Analysis. In Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART, ISBN 978-989-758-623-1, pages 276-284. DOI: 10.5220/0011658200003393

in Bibtex Style

@conference{icaart23,
author={Jieying Xue and Minh-Phuong Nguyen and Le-Minh Nguyen},
title={Emotions Relationship Modeling in the Conversation-Level Sentiment Analysis},
booktitle={Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,},
year={2023},
pages={276-284},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0011658200003393},
isbn={978-989-758-623-1},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 15th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART,
TI - Emotions Relationship Modeling in the Conversation-Level Sentiment Analysis
SN - 978-989-758-623-1
AU - Xue J.
AU - Nguyen M.
AU - Nguyen L.
PY - 2023
SP - 276
EP - 284
DO - 10.5220/0011658200003393