The Datafied Society : Studying Culture through Data

The Datafied Society Studying Culture through Data

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The ability to gather data that can be crunched by machines is valuable for studying society. The new methods needed to work it require new skills and new ways of thinking about best research practices. This book reflects on the role and usefulness of big data, challenging overly optimistic expectat...

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Detalles Bibliográficos
Otros Autores: Schäfer, Mirko Tobias, editor (editor), van Es, Karin, editor
Formato: Libro electrónico
Idioma:Inglés
Publicado: Amsterdam : Amsterdam University Press [2017]
Colección:De Gruyter Open Access ebooks.
Acceso en línea:Conectar con la versión electrónica
Ver en Universidad de Navarra:https://innopac.unav.es/record=b4446034x*spi
Tabla de Contenidos:
  • Frontmatter
  • Table of Contents
  • Acknowledgements / Schäfer, Mirko Tobias / van Es, Karin
  • Foreword / van Dijck, José
  • Introduction / van Es, Karin / Schäfer, Mirko Tobias
  • Section 1. Studying Culture through Data
  • 1. Humanistic Data Research / Masson, Eef
  • 2. Towards a 'Humanistic Cinemetrics'? / Olesen, Christian Gosvig
  • 3. Cultural Analytics, Social Computing and Digital Humanities / Manovich, Lev
  • 4. Case Study / Goddemeyer, Daniel / Stefaner, Moritz / Baur, Dominikus / Manovich, Lev
  • 5. Foundations of Digital Methods / Rogers, Richard
  • 6. Case Study / Sánchez-Querubín, Natalia
  • Section 2. Data Practices in Digital Data Analysis
  • 7. Digital Methods / Rieder, Bernhard / Röhle, Theo
  • 8. Data, Culture and the Ambivalence of Algorithms / Uricchio, William
  • 9. Unknowing Algorithms / Paßmann, Johannes / Boersma, Asher
  • 10. Social Data APIs / Puschmann, Cornelius / Ausserhofer, Julian
  • 11. How to Tell Stories with Networks / Venturini, Tommaso / Bounegru, Liliana / Jacomy, Mathieu / Gray, Jonathan
  • 12. Towards a Reflexive Digital Data Analysis / van Es, Karin / López Coombs, Nicolás / Boeschoten, Thomas
  • Section 3. Research Ethics
  • 13. Get Your Hands Dirty / van Schie, Gerwin / Westra, Irene / Schäfer, Mirko Tobias
  • 14. Research Ethics in Context / Markham, Annette / Buchanan, Elizabeth
  • 15. Datafication & Discrimination / Leurs, Koen / Shepherd, Tamara
  • Section 4. Key Ideas in Big Data Research
  • 16. The Myth of Big Data / Couldry, Nick
  • 17. Data Point Critique / Gerlitz, Carolin
  • 18. Opposing the Exceptionalism of the Algorithm / Morozov, Evgeny
  • 19. The Need for a Dialogue with Technology / Bunz, Mercedes
  • Tools
  • Notes on Contributors
  • Index.

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