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Temporal Evolution of Public Health Sentiment: A Longitudinal Analysis

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aut.relation.endpage1509
aut.relation.journalStudies in Health Technology and Informatics
aut.relation.startpage1505
aut.relation.volume329
dc.contributor.authorMadanian, Samaneh
dc.contributor.authorBakhtiari, Vahid
dc.contributor.authorFeng, Vincent
dc.date.accessioned2025-09-01T22:34:31Z
dc.date.available2025-09-01T22:34:31Z
dc.date.issued2025-08
dc.description.abstractThis study advances our understanding of public health crisis communication by conducting a longitudinal analysis. As COVID-19 has been the largest public health crisis to date, we performed sentiment analysis on it. While previous research focused on discrete time periods, our study examines the arc of pandemic-related discourse from 2020 to 2022, revealing long-term patterns in public sentiment evolution. Using advanced natural language processing techniques and temporal pattern analysis, we identify key transition points in public health discourse and sentiment, offering insights for future crisis communication strategies.
dc.identifier.citationStudies in Health Technology and Informatics, ISSN: 0926-9630 (Print); 0926-9630 (Online), IOS Press, Volume 329: MEDINFO 2025 — Healthcare Smart × Medicine Deep, 1505-1509. doi: 10.3233/SHTI251090
dc.identifier.doi10.3233/SHTI251090
dc.identifier.issn0926-9630
dc.identifier.issn0926-9630
dc.identifier.urihttp://hdl.handle.net/10292/19746
dc.languageeng
dc.publisherIOS Press
dc.relation.urihttps://ebooks.iospress.nl/doi/10.3233/SHTI251090
dc.rights© 2025 The Authors. This article is published online with Open Access by IOS Press and distributed under the terms of the Creative Commons Attribution Non-Commercial License 4.0 (CC BY-NC 4.0).
dc.rights.accessrightsOpenAccess
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.subjectDigital Health
dc.subjectDisaster Response
dc.subjectNLP
dc.subjectPublic Health
dc.subjectText Mining
dc.subject46 Information and Computing Sciences
dc.subject4608 Human-Centred Computing
dc.subjectInfectious Diseases
dc.subjectEmerging Infectious Diseases
dc.subject0807 Library and Information Studies
dc.subject1117 Public Health and Health Services
dc.subjectMedical Informatics
dc.subject4203 Health services and systems
dc.subject4601 Applied computing
dc.subject.meshCOVID-19
dc.subject.meshHumans
dc.subject.meshLongitudinal Studies
dc.subject.meshNatural Language Processing
dc.subject.meshPandemics
dc.subject.meshPublic Health
dc.subject.meshSARS-CoV-2
dc.subject.meshSocial Media
dc.subject.meshCOVID-19
dc.subject.meshLongitudinal Studies
dc.subject.meshHumans
dc.subject.meshNatural Language Processing
dc.subject.meshPublic Health
dc.subject.meshSARS-CoV-2
dc.subject.meshPandemics
dc.subject.meshSocial Media
dc.subject.meshHumans
dc.subject.meshLongitudinal Studies
dc.subject.meshPublic Health
dc.subject.meshNatural Language Processing
dc.subject.meshPandemics
dc.subject.meshSocial Media
dc.subject.meshCOVID-19
dc.subject.meshSARS-CoV-2
dc.titleTemporal Evolution of Public Health Sentiment: A Longitudinal Analysis
dc.typeJournal Article
pubs.elements-id624669

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