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Changes in the Sentiments and Metaphors in COVID-19 News Discourse (2019-2024)

  • Yolanda Honglei Guan
  • , Winnie Huiheng Zeng

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

This study investigates the diachronic changes in the sentiments and metaphorical frames in a corpus of news discourse on COVID-19 as a case study to examine the potential implication for applying sentiment analysis in corpus data and its interaction with metaphorical framing changes over time. The corpus contains COVID-19 news articles covering the entire cycle of the pandemic from 2019 to 2024 in Hong Kong. The sentiment analysis of the corpus was explicitly presented. We found that the sentiments of the news are overall objective and slightly positive. The diachronic changes and the interaction between the sentiments and metaphor polarities were discussed with empirical examples from the corpus, aiming to establish an operational approach for exploring the connection between metaphor polarities and the sentiments in large-scale of discourse data.

Original languageEnglish
Title of host publicationProceedings of the 38th Pacific Asia Conference on Language, Information and Computation
EditorsNathaniel Oco, Shirley N. Dita, Ariane Macalinga Borlongan, Jong-Bok Kim
PublisherAssociation for Computational Linguistics (ACL)
Pages810-819
Publication statusPublished - Dec 2024
Event38th Pacific Asia Conference on Language, Information and Computation, PACLIC 2024 - Hybrid, Tokyo, Japan
Duration: 7 Dec 20249 Dec 2024

Publication series

NamePACLIC - Pacific Asia Conference on Language Information and Computation
PublisherAssociation for Computational Linguistics

Conference

Conference38th Pacific Asia Conference on Language, Information and Computation, PACLIC 2024
Country/TerritoryJapan
CityHybrid, Tokyo
Period7/12/249/12/24

ASJC Scopus subject areas

  • Language and Linguistics
  • Computer Science (miscellaneous)

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