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Mendeley readers
| Chapter title |
Algorithmic Transparency via Quantitative Input Influence
|
|---|---|
| Chapter number | 4 |
| 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_4 |
| Book ISBNs |
978-3-31-954023-8, 978-3-31-954024-5
|
| Authors |
Anupam Datta, Shayak Sen, Yair Zick |
| Editors |
Tania Cerquitelli, Daniele Quercia, Frank Pasquale |
Mendeley readers
The data shown below were compiled from readership statistics for 137 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 1% |
| United Kingdom | 1 | <1% |
| Sri Lanka | 1 | <1% |
| Germany | 1 | <1% |
| Unknown | 132 | 96% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 45 | 33% |
| Student > Master | 21 | 15% |
| Researcher | 16 | 12% |
| Other | 9 | 7% |
| Student > Bachelor | 6 | 4% |
| Other | 16 | 12% |
| Unknown | 24 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 63 | 46% |
| Engineering | 12 | 9% |
| Social Sciences | 7 | 5% |
| Business, Management and Accounting | 7 | 5% |
| Arts and Humanities | 3 | 2% |
| Other | 19 | 14% |
| Unknown | 26 | 19% |