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dc.contributor.advisorSylvie, George
dc.creatorFunk, Marcus Jamesen
dc.date.accessioned2014-01-30T16:40:45Zen
dc.date.issued2013-12en
dc.date.submittedDecember 2013en
dc.identifier.urihttp://hdl.handle.net/2152/22983en
dc.descriptiontexten
dc.description.abstractThis dissertation explores deviance, operationalized through news factors, among American community weekly, community daily, large daily, and national daily newspaper websites and social media posts. Computerized quantitative analysis indicates that circulation size makes little to no significant difference concerning the publication of deviant news factors; smaller circulation sizes are significantly related to the publication of news concerning local communities, but not egalitarian news factors generally. Qualitative, structured interviews of community newspaper editors and publishers illustrate a different agenda - a clear focus for news on "regular people and routine events," arguably egalitarianism, over news on "unusual people or extraordinary events," arguably deviance. This indicates a need for further evaluation and development of computerized content analysis, gatekeeping theory, and the community newspaper industry. Results also suggest a need to reconsider and re-evaluate normative deviance as a concept and point to two potential theoretical developments: considering a Deviant-Egalitarian Spectrum and drastically broadening the current fringe focus of deviance research.en
dc.format.mimetypeapplication/pdfen
dc.language.isoen_USen
dc.subjectCommunity journalismen
dc.subjectDevianceen
dc.subjectGatekeepingen
dc.subjectNewspapersen
dc.subjectNews websitesen
dc.subjectSocial mediaen
dc.subjectFacebooken
dc.subjectTwitteren
dc.titleAnalyzing content deviance in American community journalism websites and social mediaen
dc.date.updated2014-01-30T16:40:46Zen
dc.description.departmentJournalismen
thesis.degree.departmentJournalismen
thesis.degree.disciplineJournalismen
thesis.degree.grantorThe University of Texas at Austinen
thesis.degree.levelDoctoralen
thesis.degree.nameDoctor of Philosophyen


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