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dc.contributor.advisorDrew, Eileen
dc.contributor.authorLeavy, Susan
dc.date.accessioned2017-06-01T13:33:02Z
dc.date.available2017-06-01T13:33:02Z
dc.date.issued2014
dc.identifier.citationSusan Leavy, 'Detecting gender bias in the coverage of politicians in Irish newspapers using automated text classification', [thesis], Trinity College (Dublin, Ireland). School of Computer Science & Statistics, 2014, pp 310
dc.identifier.otherTHESIS 10564
dc.identifier.urihttp://hdl.handle.net/2262/80288
dc.description.abstractThis thesis presents an investigation of whether there is evidence of gender bias in the coverage of politicians in Irish newspapers. Text-analysis techniques including natural language processing and machine learning are used to analyse newspaper content and highlighting differences in the coverage of male and female politicians. These differences are then analysed to identify any evidence of gender bias.
dc.format1 volume
dc.language.isoen
dc.publisherTrinity College (Dublin, Ireland). School of Computer Science & Statistics
dc.relation.isversionofhttp://stella.catalogue.tcd.ie/iii/encore/record/C__Rb16144093
dc.subjectComputer Science & Statistics, Ph.D.
dc.subjectPh.D. Trinity College Dublin
dc.titleDetecting gender bias in the coverage of politicians in Irish newspapers using automated text classification
dc.typethesis
dc.type.supercollectionthesis_dissertations
dc.type.supercollectionrefereed_publications
dc.type.qualificationlevelDoctoral
dc.type.qualificationnameDoctor of Philosophy (Ph.D.)
dc.rights.ecaccessrightsopenAccess
dc.format.extentpaginationpp 310
dc.description.noteTARA (Trinity's Access to Research Archive) has a robust takedown policy. Please contact us if you have any concerns: rssadmin@tcd.ie


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