Studying Culture through Data
E-Book, Englisch, 267 Seiten
ISBN: 978-90-485-3101-1
Verlag: Amsterdam University Press
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)
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Weitere Infos & Material
Acknowledgements Foreword Introduction: New Brave World Karin van Es and Mirko Tobias Schäfer Section 1: Studying Culture through Data Humanistic Data Research: An Encounter between Epistemic Traditions Eef Masson Towards a 'Humanistic Cinemetrics'? Christian Gosvig Olesen Cultural Analytics, Social Computing, and Digital Humanities Lev Manovich Case Study: On Broadway Daniel Goddemeyer, Moritz Stefaner, Dominikus Baur, and Lev Manovich Foundations of Digital Methods: Query Design Richard Rogers Case Study: Webs and Streams: Mapping Issue-Networks Using Hyperlinks, Hashtags, and (Potentially) Embedded Content Natalia Sánchez-Querubín Section 2: Data Practices in Digital Data Analysis Digital Methods: From Challenges to Bildung Bernhard Rieder and Theo Röhle Data, Culture, and the Ambivalence of Algorithms William Uricchio Unknowing Algorithms: On Transparency of Un-operable Black Boxes Johannes Paßmann and Asher Boersma Social Data APIs: Origin, Types, Issues Cornelius Puschmann and Julian Ausserhofer How to Tell Stories with Networks: Exploring the Narrative Affordances of Graphs with the Iliad Tommaso Venturini, Liliana Bounegru, Mathieu Jacomy, and Jonathan Gray Towards a Reflexive Digital Data Analysis Karin van Es, Nicolás López Coombs and Thomas Boeschoten Section 3: Research Ethics Get Your Hands Dirty: Research Ethics in an Age of Big Data: How Digital Methods and 'Big Data' Practices Challenge Traditional Guidelines for Research Integrity Gerwin van Schie, Irene Westra, and Mirko Tobias Schäfer Research Ethics in Context: Decision-Making in Digital Research Annette Markham and Elizabeth Buchanan Data and Discrimination Koen Leurs and Tamara Shepherd Section 4: Key Ideas in Big Data Research: The Myth of Big Data, Data Point Critique, Algorithmic Exceptionalism of Algorithms and the Need for a Dialogue with Technology The Myth of Big Data Nick Couldry Data-Point Critique Carolin Gerlitz Opposing the Exceptionalism of the Algorithm Evgeny Morozov The Need for a Dialogue with Technology Mercedes Bunz Tools Notes on Contributors Index