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Normalization and differentiation in Google News: a multi-method analysis of the world's largest news aggregator
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Wang, Qun. Normalization and differentiation in Google News: a multi-method analysis of the world's largest news aggregator. Retrieved from https://doi.org/doi:10.7282/t3-cn0p-6g66

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TitleNormalization and differentiation in Google News: a multi-method analysis of the world's largest news aggregator
NameWang, Qun (author); Keith, Susan (chair); Napoli, Philip (internal member); Weber, Matthew (internal member); Lewis, Seth (outside member); Rutgers University; School of Graduate Studies
Date Created2020
Other Date2020-01 (degree)
SubjectCommunication, Information and Library Studies, News Web sites, Google (Firm)
Extent1 online resource (iii, 256 pages) : illustrations
DescriptionThis dissertation examines the history, evolution, and influence of Google News—Google’s news aggregation service—from the late 1990s to 2019. There are scattered studies about Google News, but no systematic and substantive research on what is, at this writing, its nearly two decades of existence. Those two decades happened to be a period of time that witnessed the intense digital transformation of the media industry and our society. Both the object of the study and the timeframe this study examines are significant to understand the changing media and technology environment in the 21st century. Drawing on normalization and differentiation theoretical frameworks, this dissertation combines traditional research methods and computational approaches to conduct historical research, web archival analysis, legal analysis, algorithm analysis, and more. In six chapters, this dissertation traces the origin and early history of Google News; the structural, visual, and functional evolution on the Google News homepage design since its launch in 2002; disputes about Google and its news aggregation service in different parts of the world; Google’s news-related technologies and algorithms; and Google’s systematic initiatives in the news area and their influences. Based on the analysis of the normalization and differentiation trends and the driving forces behind these trends, this study proposes an N-D-N theoretical model that conceptualizes Google’s development in the news area and the interaction between Google and the news industry. The dissertation concludes with a discussion about the implications of the N-D-N model for policymaking on platform governance and the future of journalism. Using Google News as a case study, this dissertation provides a snapshot of the changing media landscape in the digital era. It also makes theoretical and empirical contributions to the ongoing conversation about the interrelationship between digital platforms and the traditional media industry.
NotePh.D.
NoteIncludes bibliographical references
Genretheses, ETD doctoral
Persistent URLhttps://doi.org/doi:10.7282/t3-cn0p-6g66
LanguageEnglish
CollectionSchool of Graduate Studies Electronic Theses and Dissertations
Organization NameRutgers, The State University of New Jersey
RightsThe author owns the copyright to this work.
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