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Transparent Data Mining for Big and Small Data

Overview of attention for book
Attention for Chapter 2: Enabling Accountability of Algorithmic Media: Transparency as a Constructive and Critical Lens
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Mentioned by

twitter
2 tweeters

Citations

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9 Dimensions

Readers on

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8 Mendeley
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Chapter title
Enabling Accountability of Algorithmic Media: Transparency as a Constructive and Critical Lens
Chapter number 2
Book title
Transparent Data Mining for Big and Small Data
Published by
Springer International Publishing, January 2017
DOI 10.1007/978-3-319-54024-5_2
Book ISBNs
978-3-31-954023-8, 978-3-31-954024-5
Authors

Nicholas Diakopoulos

Editors

Tania Cerquitelli, Daniele Quercia, Frank Pasquale

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 38%
Lecturer 1 13%
Student > Doctoral Student 1 13%
Student > Master 1 13%
Unknown 2 25%
Readers by discipline Count As %
Computer Science 3 38%
Unspecified 1 13%
Economics, Econometrics and Finance 1 13%
Social Sciences 1 13%
Unknown 2 25%