Sentiment analysis of online responses in the performing arts with large language models

Baekryun Seong, Kyungwoo Song

Research output: Contribution to journalArticlepeer-review

5 Citations (Scopus)

Abstract

Opinion mining is a technique extracting and analyzing people's opinions from online communities, and sentiment analysis is a kind of opinion mining analyzing attitudes of people toward an object, whether positive, negative, or neutral. Sentiment analysis has evolved alongside natural language processing models and applied to targets such as movie reviews. However, the performing arts have not been subjected to sentiment analysis as movie reviews, despite the apparent need for it. In this study, we used the Korean Funnel Transformer11 language model to perform sentiment analysis on performing arts. This study looks at people's reactions to performing arts in online communities, not just whether they agree or disagree, and shows the problems with applying existing sentiment analysis to performing arts.

Original languageEnglish
Article numbere22457
JournalHeliyon
Volume9
Issue number12
DOIs
Publication statusPublished - 2023 Dec

Bibliographical note

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© 2023 The Authors

All Science Journal Classification (ASJC) codes

  • General

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