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Mendeley readers
| Title |
Network Based Scoring Models to Improve Credit Risk Management in Peer to Peer Lending Platforms
|
|---|---|
| Published in |
Frontiers in Artificial Intelligence, May 2019
|
| DOI | 10.3389/frai.2019.00003 |
| Pubmed ID | |
| Authors |
Paolo Giudici, Branka Hadji-Misheva, Alessandro Spelta |
Mendeley readers
The data shown below were compiled from readership statistics for 91 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 91 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 10 | 11% |
| Lecturer | 10 | 11% |
| Student > Ph. D. Student | 8 | 9% |
| Researcher | 5 | 5% |
| Unspecified | 5 | 5% |
| Other | 12 | 13% |
| Unknown | 41 | 45% |
| Readers by discipline | Count | As % |
|---|---|---|
| Business, Management and Accounting | 15 | 16% |
| Economics, Econometrics and Finance | 9 | 10% |
| Computer Science | 9 | 10% |
| Unspecified | 5 | 5% |
| Agricultural and Biological Sciences | 2 | 2% |
| Other | 9 | 10% |
| Unknown | 42 | 46% |