Disambiguating Emotional Connotations of Words Using Contextualized Word Representations

Akram Sadat Hosseini, Steffen Staab


Abstract
Understanding emotional nuances in written content is crucial for effective communication; however, the context-dependent nature of language poses challenges in precisely discerning emotions in text. This study contributes to the understanding of how the emotional connotations of a word are influenced by the sentence context in which it appears. Leveraging the contextual understanding embedded in contextualized word representations, we conduct an empirical investigation to (i) evaluate the varying abilities of these representations in distinguishing the diverse emotional connotations evoked by the same word across different contexts, (ii) explore potential biases in these representations toward specific emotions of a word, and (iii) assess the capability of these representations in estimating the number of emotional connotations evoked by a word in diverse contexts. Our experiments, utilizing four popular models—BERT, RoBERTa, XLNet, and GPT-2—and drawing on the GoEmotions and SemEval 2018 datasets, demonstrate that these models effectively discern emotional connotations of words. RoBERTa, in particular, shows superior performance and greater resilience against biases. Our further analysis reveals that disambiguating the emotional connotations of words significantly enhances emotion identification at the sentence level.
Anthology ID:
2024.starsem-1.21
Volume:
Proceedings of the 13th Joint Conference on Lexical and Computational Semantics (*SEM 2024)
Month:
June
Year:
2024
Address:
Mexico City, Mexico
Editors:
Danushka Bollegala, Vered Shwartz
Venue:
*SEM
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
264–277
Language:
URL:
https://aclanthology.org/2024.starsem-1.21
DOI:
Bibkey:
Cite (ACL):
Akram Sadat Hosseini and Steffen Staab. 2024. Disambiguating Emotional Connotations of Words Using Contextualized Word Representations. In Proceedings of the 13th Joint Conference on Lexical and Computational Semantics (*SEM 2024), pages 264–277, Mexico City, Mexico. Association for Computational Linguistics.
Cite (Informal):
Disambiguating Emotional Connotations of Words Using Contextualized Word Representations (Hosseini & Staab, *SEM 2024)
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PDF:
https://preview.aclanthology.org/jeptaln-2024-ingestion/2024.starsem-1.21.pdf