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Post, Mine, Repeat: Social Media Data Mining Becomes Ordinary 1st ed. 2016 [Kõva köide]

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  • Formaat: Hardback, 262 pages, kõrgus x laius: 210x148 mm, kaal: 4653 g, 15 Illustrations, color; XV, 262 p. 15 illus. in color., 1 Hardback
  • Ilmumisaeg: 03-Jun-2016
  • Kirjastus: Palgrave Macmillan
  • ISBN-10: 113735397X
  • ISBN-13: 9781137353979
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Post, Mine, Repeat: Social Media Data Mining Becomes Ordinary 1st ed. 2016Suurem pilt
  • Formaat: Hardback, 262 pages, kõrgus x laius: 210x148 mm, kaal: 4653 g, 15 Illustrations, color; XV, 262 p. 15 illus. in color., 1 Hardback
  • Ilmumisaeg: 03-Jun-2016
  • Kirjastus: Palgrave Macmillan
  • ISBN-10: 113735397X
  • ISBN-13: 9781137353979
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9781137353979.html
Märksõnad:
In this book, Helen Kennedy argues that as social media data mining becomes more and more ordinary, as we post, mine and repeat, new data relations emerge. These new data relations are characterised by a widespread desire for numbers and the troubling consequences of this desire, and also by the possibility of doing good with data and resisting data power, by new and old concerns, and by instability and contradiction. Drawing on action research with public sector organisations, interviews with commercial social insights companies and their clients, focus groups with social media users and other research, Kennedy provides a fascinating and detailed account of living with social media data mining inside the organisations that make up the fabric of everyday life.

Arvustused

One of the key features of the book is the way each chapter concludes with the pros and cons, the concerns and ethical issues, of the strategies, tactics, and issues raised within. Rather than glossing over ethical issues, the book continually reengages with the most pressing questions of data mining, keeping concerns specific and grounded in research tactics, a feature that will help the book maintain relevance for future researchers, regardless of changes to social media platforms and data relations. (Alisha Karabinus, Convergence, June 20, 2019) I am grateful that this book highlights so many aspects of social data mining, including the quantified self movement and the Seeing Data project that identify ways in which ordinary citizens can engage more with the politics of data mining . Media studies students and professors seeking a snapshot of scholarship on social media data mining will find this text incredibly helpful asan aggregator of a vast and ideological varied body of scholarship. (Daniel Keyes, PsycCRITIQUES, Vol. 61 (51), December, 2016)

1 Social Media Data Mining Becomes Ordinary
1(18)
Data Abundance and Its Consequences
1(10)
Researching Ordinary Social Media Data Mining
11(8)
2 Why Study Social Media Data Mining?
19(22)
Introduction
19(2)
Four Characteristics of Social Media: Participation, Sharing, Intimacy and Monetisation
21(8)
What Is Social Media Data Mining?
29(9)
Conclusion
38(3)
3 What Should Concern Us About Social Media Data Mining? Key Debates
41(26)
Introduction
41(3)
Critiques of (Social Media) Data Mining
44(9)
Less Privacy, More Surveillance
44(3)
Discrimination and Control
47(2)
Methodological Concerns
49(3)
Issues of Access and Inequality
52(1)
Seeking Agency in Data Mining Structures
53(11)
Worker Agency
56(2)
User Agency
58(2)
Techno-agency
60(2)
Postscript on Agency: Acting Ethically in Times of Data Mining
62(2)
Conclusion
64(3)
4 Public Sector Experiments with Social Media Data Mining
67(32)
Introduction
67(3)
Action Research and the Production of Publics
70(6)
Knowing and Forming Publics
70(1)
Action-Researching Public Uses of Social Media Data Mining
71(5)
Social Media Data Mining for the Public Good?
76(11)
Uses of Social Media Data Mining
76(3)
Understanding Publics, Desiring Numbers
79(8)
Constituting Publics
87(7)
How Keywords Constitute Publics
87(2)
How Expertise (Or Its Absence) Constitutes Publics
89(2)
Working Around Data Non-abundance to Constitute Publics
91(3)
Conclusion: What Should Concern Us About Public Sector Social Media Data Mining?
94(5)
5 Commercial Mediations of Social Media Data
99(30)
Introduction
99(5)
The Practices of Intermediary Insights Companies and the Concerns of Workers
104(7)
Who Companies and Interviewees Are
104(2)
What Companies and Interviewees Do
106(5)
Social Media Data Mining as Moral and Economic Practice
111(13)
Accessing `Public' Data
113(3)
Drawing Ethical Boundaries
116(2)
Transparency as Ethics
118(2)
Who Benefits from Social Media Data Mining?
120(2)
Regulation as Ethical Solution?
122(2)
Conclusion: Concerns and Ethics in Commercial Social Media Data Mining Practice
124(5)
6 What Happens to Mined Social Media Data?
129(30)
Introduction
129(3)
Interviewees, Organisations, and Their Uses of Social Media Data Mining
132(5)
The Consequences of Social Media Data Mining
137(18)
Concrete Action and Organisational Complexity
137(4)
Organisational Change and the Quality of Working Life
141(3)
Data Evangelism and `The Fetishism of the 1000'
144(7)
`The Parasite on the Rhino'? Reflections on Ethical Issues
151(4)
Conclusion: Consequences and Concerns
155(4)
7 Fair Game? User Evaluations of Social Media Data Mining
159(30)
Introduction
159(3)
What Do Users Think? Studies of Users' Views
162(7)
Quantitative Studies of Attitudes to Digital Data Tracking
162(4)
Qualitative Studies of Social Media User and Attitudes to Social Media Data Mining, and the `Contextual Integrity' Framework
166(3)
Focus Group Methods for Researching User Perspectives
169(2)
What Do Users Think? Focus Group Findings
171(14)
Diverse Perspectives
171(8)
Common Threads: Concerns About Fairness
179(6)
What Concerns Users? Fairness, Transparency, Contextual Integrity
185(4)
8 Doing Good with Data: Alternative Practices, Elephants in Rooms
189(32)
Introduction
189(2)
Elephants in Rooms: Academic Social Media Data Mining
191(11)
Overview of Academic Social Media Data Mining
191(2)
Concerns and Criticisms
193(5)
Un-Black-Boxing Social Media Data Mining
198(4)
Alternative Practices: Data Activism
202(15)
The Open Data Movement
202(3)
Re-active and Pro-active Data Activism
205(7)
Doing Good, Or Doing Bad, Through Data Activism?
212(5)
Conclusion
217(4)
9 New Data Relations and the Desire for Numbers
221(16)
Established Concerns
222(2)
Emerging Concerns
224(6)
The Desire for Numbers
224(1)
(Not) Thinking Critically About Data-making
225(3)
Work Effects
228(2)
Doing Good with Data
230(2)
New Data Relations
232(2)
Doing Better with Data
234(3)
Bibliography 237(18)
Index 255
Helen Kennedy is Professor of Digital Society at the University of Sheffield, UK. She has researched and published widely across the field of digital media, from web homepages to data visualisations, from race, class, gender inequality to learning disability and web accessibility, from web design to social media data mining.