The Datafied Society (eBook, PDF)

Studying Culture through Data
Redaktion: Schäfer, Mirko Tobias; Es, Karin

• Format: PDF

Produktbeschreibung

As machine-readable data comes to play an increasingly important role in everyday life, researchers find themselves with rich resources for studying society. The novel methods and tools needed to work with such data require not only new knowledge and skills, but also a new way of thinking about best research practices. This book critically reflects on the role and usefulness of big data, challenging overly optimistic expectations about what such information can reveal, introducing practices and methods for its analysis and visualisation, and raising important political and ethical questions regarding its collection, handling, and presentation.

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Produktdetails

• Verlag: Taylor & Francis eBooks
• Seitenzahl: 268
• Erscheinungstermin: 1. Oktober 2025
• Englisch
• ISBN-13: 9781040778463
• Artikelnr.: 75569301

Autorenporträt

Mirko Tobias Schäfer is Associate Professor of AI, Data & Society at Utrecht University's research area 'Governing the Digital Society' and the Department for Information and Computing Sciences. Mirko is co-founder and Sciences lead of the Data School. He studies the datafication of public management and engages in the development of responsible and accountable AI and data practices. Karin van Es is Associate Professor of Media and Culture Studies and project lead Humanities at Data School, both at Utrecht University.

Inhaltsangabe

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.