A Computational Content Analysis on Representation in Mental Health News Media with Global Perspectives

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dc.authorscopusid57219483972
dc.contributor.authorDursun, A.D.
dc.date.accessioned2024-07-18T20:16:44Z
dc.date.available2024-07-18T20:16:44Z
dc.date.issued2023
dc.description23rd International Conference on Computational Science and Its Applications, ICCSA 2023 -- 3 July 2023 through 6 July 2023 -- Athens -- 297179en_US
dc.description.abstractMedia representations can provide important symbolic resources in the construction of perception and agendas in diverse domains particularly concerning public health and social awareness. In view of this standpoint, dominant media frames are said to be powerful in defining social problems and shaping public discourses. The majority of the relevant literature demonstrates that representations of people with mental disorder are often negative, individuals being depicted in a passive role. A grammatical analysis of language use in press reveals different perspectives regarding the assignment of a more or less prominent role. The use of active and passive verb voice is one constituent of such analysis. Framing process constitutes another mode of analysis of news media content, which is stated to be dynamic in the concept of communication. Accordingly, this study aims to provide insights into the representation of individuals that experience mental health problems. For this purpose, newspaper stories are analyzed by examining the volume and content of a sample of selected news stories on mental illness in Türkiye for a time period of six years. Six national daily newspapers make up the sample of the study which provides a content analysis on the news media dataset. The analysis results demonstrate statistical findings on the depiction of people with mental disorder. Based on the findings and considering the sensitivity of the issue, it can be noted that more emphasis can be placed on humanizing mental illness by indicating that mental disorder is real, common and possible to be treated. In addition, coverage of other success stories with positive frames can be an alternative way to balance the multitude of news stories that link mental illness with violence or other negative elements. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.en_US
dc.description.sponsorshipAMCS; Canada University of Coimbra; DOE Ames Laboratory; India/USA University of Perugia; Instituto Tecnológico de Informática, Spain Kausan University of Technology, Lithuania London South Bank University, UK Memorial University of Newfoundland; Italy Erciyes University; Italy Sungkyunkwan University; Italy University of Minho; Korea Polytechnic Institute of Viana do Castelo; Korea Sunway University, Malaysia Sungkyunkwan University; Portugal Federal University of Bahia; Portugal National Centre for Biotechnology; Portugal University of Almeria, Spain University of Salerno; Portugal University of Aveiro; Portugal University of Beira Interior; Portugal University of L’Aquila; Provence-Alpes-Côte d’Azur; School of Rural, Surveying and Geoinformatics Engineering; Turkey University of Naples; Tutut Herawan; VSTU, (60/438-22); Center for Strategic and International Studies, CSIS; Council for Scientific and Industrial Research, South Africa, CSIR; Fundação para a Ciência e a Tecnologia, FCT, (UIDB/00013/2020, UIDB/03182/2020, UIDB/04106/2020, UIDP/00013/2020, UIDP/04106/2020); Coordenação de Aperfeiçoamento de Pessoal de Nível Superior, CAPES; Russian Academy of Sciences, ???, (FWZZ-2022-0022); Ministero dell’Istruzione, dell’Università e della Ricerca, MIUR, (20178XXKFY); Conselho Nacional de Desenvolvimento Científico e Tecnológico, CNPq; Saint Petersburg State University, SPbU, (94062114); Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro, FAPERJ, (200.850/2021, 201.013/2022, 211.000/2021); Universidade Nova de Lisboa, UNL; Russian Science Foundation, RSF, (21-71-20003); Università degli Studi di Perugia; School of Electrical and Computer Engineering,University of Tehran, ECE, UT; Instituto Politécnico de Bragança, IPB; National Technical University of Athens, NTUA; Anhui University of Finance and Economics, AUFEen_US
dc.identifier.doi10.1007/978-3-031-37105-9_8
dc.identifier.endpage115en_US
dc.identifier.isbn978-303137104-2
dc.identifier.issn0302-9743
dc.identifier.scopus2-s2.0-85164976467en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage105en_US
dc.identifier.urihttps://doi.org/10.1007/978-3-031-37105-9_8
dc.identifier.urihttps://hdl.handle.net/11411/6234
dc.identifier.volume14104 LNCSen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherSpringer Science and Business Media Deutschland GmbHen_US
dc.relation.ispartofLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)en_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectCategorical Level Of Representationen_US
dc.subjectComputational And Multi-Way Frequency Analysisen_US
dc.subjectComputational Content Analysisen_US
dc.subjectComputational Journalismen_US
dc.subjectComputational Linguisticsen_US
dc.subjectDegree Of Agencyen_US
dc.subjectGrammatical Analysesen_US
dc.subjectJournalistic News Mediaen_US
dc.subjectMental Health Newsen_US
dc.subjectNews Framesen_US
dc.subjectPublic Discoursesen_US
dc.subjectSystematic Language Descriptionen_US
dc.subjectDiseasesen_US
dc.subjectNewsprinten_US
dc.subjectCategorical Level Of Representationen_US
dc.subjectComputational And Multi-Way Frequency Analyseen_US
dc.subjectComputational Content Analyseen_US
dc.subjectComputational Contentsen_US
dc.subjectComputational Journalismen_US
dc.subjectContent Analysisen_US
dc.subjectDegree Of Agencyen_US
dc.subjectGrammatical Analyzeen_US
dc.subjectJournalistic News Mediumen_US
dc.subjectLanguage Descriptionen_US
dc.subjectMental Healthen_US
dc.subjectMental Health Newsen_US
dc.subjectMulti-Way Frequency Analysisen_US
dc.subjectNews Frameen_US
dc.subjectNews Mediaen_US
dc.subjectPublic Discourseen_US
dc.subjectSystematic Language Descriptionen_US
dc.subjectComputational Linguisticsen_US
dc.titleA Computational Content Analysis on Representation in Mental Health News Media with Global Perspectives
dc.typeConference Object

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