EmoLLMs: A Series of Emotional Large Language Models and Annotation Tools for Comprehensive Affective Analysis-Reference-Cited by-同舟云学术

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EmoLLMs: A Series of Emotional Large Language Models and Annotation Tools for Comprehensive Affective Analysis

Published:2024-08-24 Issue: Volume:33 Page:5487-5496
ISSN:
Container-title:Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
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Author:

Liu Zhiwei¹^ORCID,Yang Kailai¹^ORCID,Xie Qianqian¹^ORCID,Zhang Tianlin¹^ORCID,Ananiadou Sophia²^ORCID

Affiliation:

1. The University of Manchester, Manchester, United Kingdom

2. The University of Manchester & Artificial Intelligence Research Center, Manchester, United Kingdom

Funder

The Centre for Digital Trust and Society at the University of Manchester

The Manchester-Melbourne-Toronto Research Fund

University Of Manchester

New Energy and Industrial Technology Development Organization (NEDO)

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3637528.3671552

Reference58 articles.

1. How Intense Are You? Predicting Intensities of Emotions and Sentiments using Stacked Ensemble [Application Notes]

2. Analyzing Amazon Products Sentiment: A Comparative Study of Machine and Deep Learning, and Transformer-Based Techniques

3. BELLEGroup. 2023. BELLE: Be Everyone's Large Language model Engine. https://github.com/LianjiaTech/BELLE.

4. A BERT Framework to Sentiment Analysis of Tweets

5. Readers vs. Writers vs. Texts: Coping with Different Perspectives of Text Understanding in Emotion Annotation

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