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Cited 14 time in webofscience Cited 17 time in scopus
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Learning from disagreement on social media: The mediating role of like-minded and cross-cutting discussion and the moderating role of fact-checking

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dc.contributor.authorLin, Han-
dc.contributor.authorKim, Yonghwan-
dc.date.accessioned2024-09-26T17:00:45Z-
dc.date.available2024-09-26T17:00:45Z-
dc.date.issued2023-02-
dc.identifier.issn0747-5632-
dc.identifier.issn1873-7692-
dc.identifier.urihttps://scholarworks.dongguk.edu/handle/sw.dongguk/25823-
dc.description.abstractSocial networking sites (SNSs) have the potential to be effective in facilitating exposure to disagreement. However, whether exposure to disagreement leads to fostering democratic deliberation has received little attention. Drawing on a national panel survey, this study explores the cognitive processes by which social media news users learn new perspectives from disagreement via the mediating role of interpersonal discussion and the moderating role of fact-checking. The results reveal that social media news use is positively associated with learning from disagreement, and this relationship is mediated by like-minded and cross-cutting discussions. Specifically, while cross-cutting discussions facilitate individuals' understanding and learning of opposing viewpoints, like-minded discussions hinder this process. Furthermore, fact-checking has the potential to reinforce not only tolerant attitudes toward opposing viewpoints but also individuals' pre-existing beliefs and impede learning from disagreement. The mixed effect of fact-checking depends on the type of interpersonal discussion taking place. In light of these findings, we discuss the contributions and shortcomings of SNSs and fact-checking behavior in terms of the ideals of deliberative democracy.-
dc.format.extent11-
dc.language영어-
dc.language.isoENG-
dc.publisherElsevier Ltd-
dc.titleLearning from disagreement on social media: The mediating role of like-minded and cross-cutting discussion and the moderating role of fact-checking-
dc.typeArticle-
dc.publisher.location네델란드-
dc.identifier.doi10.1016/j.chb.2022.107558-
dc.identifier.scopusid2-s2.0-85145575802-
dc.identifier.wosid000901491700014-
dc.identifier.bibliographicCitationComputers in Human Behavior, v.139, pp 1 - 11-
dc.citation.titleComputers in Human Behavior-
dc.citation.volume139-
dc.citation.startPage1-
dc.citation.endPage11-
dc.type.docTypeArticle-
dc.description.isOpenAccessN-
dc.description.journalRegisteredClassssci-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaPsychology-
dc.relation.journalWebOfScienceCategoryPsychology, Multidisciplinary-
dc.relation.journalWebOfScienceCategoryPsychology, Experimental-
dc.subject.keywordPlusPOLITICAL DISAGREEMENT-
dc.subject.keywordPlusNETWORK HETEROGENEITY-
dc.subject.keywordPlusNEWS-
dc.subject.keywordPlusCOMMUNICATION-
dc.subject.keywordPlusINFORMATION-
dc.subject.keywordPlusCITIZENS-
dc.subject.keywordPlusEXPOSURE-
dc.subject.keywordPlusPARTISAN-
dc.subject.keywordPlusIMPACT-
dc.subject.keywordPlusMATTER-
dc.subject.keywordAuthorSocial media news-
dc.subject.keywordAuthorLearning from disagreement-
dc.subject.keywordAuthorFact -checking-
dc.subject.keywordAuthorLike-minded discussion-
dc.subject.keywordAuthorCross -cutting discussion-
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