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Cited 3 time in webofscience Cited 3 time in scopus
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The Role of Emotions Intensity in Helpfulness of Online Physician Reviews

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dc.contributor.authorShah, Adnan Muhammad-
dc.contributor.authorLee, KangYoon-
dc.date.accessioned2021-11-04T00:40:13Z-
dc.date.available2021-11-04T00:40:13Z-
dc.date.created2021-11-04-
dc.date.issued2022-03-
dc.identifier.issn1079-8587-
dc.identifier.urihttps://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/82583-
dc.description.abstractOnline physician reviews (OPRs) critically influence the patients' consultation decisions on physician rating websites. The increasing number of OPRs contributes to the challenge of information overload. The worth of development needs to be explored further. Based on the OPRs collected from RateMDs and Healthgrades, and Plutchik's wheel on human emotions framework, the purpose of this study was to examine the impact of emotional intensity (positive and negative) incorporated in OPRs on review helpfulness (RH). The proposed model was empirically tested using data from two physician rating websites and applying a mixed-methods approach (text mining and econometrics). The results suggested that anger, disgust, and fear (negative emotions), while joy, anticipation, and trust (positive emotions) significantly contributed to the perceived RH. Moreover, the patient's disease severity moderated the association between negative emotions (anger and disgust), or positive emotions (joy and trust) and the perceived RH. Anger incorporated in an OPR has a more negative impact on perceived RH for severe diseases than the mild diseases. The findings contributed to the significance of emotions in OPRs from an innovative perspective and provided practical insights for health rating platform owners to help patients in expressing their emotions more precisely.-
dc.language영어-
dc.language.isoen-
dc.publisherTECH SCIENCE PRESS-
dc.relation.isPartOfINTELLIGENT AUTOMATION AND SOFT COMPUTING-
dc.titleThe Role of Emotions Intensity in Helpfulness of Online Physician Reviews-
dc.typeArticle-
dc.type.rimsART-
dc.description.journalClass1-
dc.identifier.wosid000709899600005-
dc.identifier.doi10.32604/iasc.2022.019666-
dc.identifier.bibliographicCitationINTELLIGENT AUTOMATION AND SOFT COMPUTING, v.31, no.3, pp.1719 - 1735-
dc.description.isOpenAccessN-
dc.identifier.scopusid2-s2.0-85118666697-
dc.citation.endPage1735-
dc.citation.startPage1719-
dc.citation.titleINTELLIGENT AUTOMATION AND SOFT COMPUTING-
dc.citation.volume31-
dc.citation.number3-
dc.contributor.affiliatedAuthorShah, Adnan Muhammad-
dc.contributor.affiliatedAuthorLee, KangYoon-
dc.type.docTypeArticle-
dc.subject.keywordAuthorReview helpfulness-
dc.subject.keywordAuthoremotional intensity-
dc.subject.keywordAuthordiscrete emotions-
dc.subject.keywordAuthorphysician reviews-
dc.subject.keywordAuthordisease severity-
dc.subject.keywordPlusPERCEIVED HELPFULNESS-
dc.subject.keywordPlusPRODUCT REVIEWS-
dc.subject.keywordPlusINFORMATION-
dc.subject.keywordPlusDETERMINANTS-
dc.subject.keywordPlusOPTIMIZATION-
dc.subject.keywordPlusJUDGMENT-
dc.subject.keywordPlusSTYLE-
dc.subject.keywordPlusFEAR-
dc.relation.journalResearchAreaAutomation & Control Systems-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalWebOfScienceCategoryAutomation & Control Systems-
dc.relation.journalWebOfScienceCategoryComputer Science, Artificial Intelligence-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
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