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dc.rights.licenseCC-BY-NC-ND
dc.contributor.advisorSchäfer, M.T.
dc.contributor.authorWeghorst, M.T.C.
dc.date.accessioned2015-09-17T17:00:54Z
dc.date.available2015-09-17T17:00:54Z
dc.date.issued2015
dc.identifier.urihttps://studenttheses.uu.nl/handle/20.500.12932/23633
dc.description.abstractIn this explorative thesis, I will show how I used a dataset of 50 million tweets written during the 2014 World Cup to try to answer prevailing questions about the current media landscape. The focus, however, is not on the results of these case studies but on the process of getting to them. As I was continually confronted with making subjective decisions and with questions about the validity of results, I developed awareness of the fact that data and digital methods are never fully neutral. I extended Daston and Galison’s concepts of mechanical objectivity and trained judgment to include digital methods, introducing computed objectivity and trained data judgment. Finally, I argue that it is crucial for media scholars to develop a critical stance towards big data research.
dc.description.sponsorshipUtrecht University
dc.format.extent2822645
dc.format.mimetypeapplication/pdf
dc.language.isoen
dc.titleComputed Objectivity: A Critical Reflection on Using Digital Methods in the Humanities
dc.type.contentMaster Thesis
dc.rights.accessrightsOpen Access
dc.subject.keywordsTwitter, digital methods, objectivity, trained judgment
dc.subject.courseuuNieuwe media en digitale cultuur


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