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Mendeley readers
| Chapter title |
Predicting Corporate Credit Ratings Using Content Analysis of Annual Reports – A Naïve Bayesian Network Approach
|
|---|---|
| Chapter number | 4 |
| Book title |
Enterprise Applications, Markets and Services in the Finance Industry
|
| Published by |
Springer International Publishing, January 2017
|
| DOI | 10.1007/978-3-319-52764-2_4 |
| Book ISBNs |
978-3-31-952763-5, 978-3-31-952764-2
|
| Authors |
Petr Hajek, Vladimir Olej, Ondrej Prochazka |
| Editors |
Stefan Feuerriegel, Dirk Neumann |
Mendeley readers
The data shown below were compiled from readership statistics for 30 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 30 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 9 | 30% |
| Researcher | 4 | 13% |
| Student > Ph. D. Student | 4 | 13% |
| Student > Doctoral Student | 2 | 7% |
| Professor | 1 | 3% |
| Other | 3 | 10% |
| Unknown | 7 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Business, Management and Accounting | 6 | 20% |
| Computer Science | 5 | 17% |
| Engineering | 3 | 10% |
| Economics, Econometrics and Finance | 3 | 10% |
| Social Sciences | 2 | 7% |
| Other | 2 | 7% |
| Unknown | 9 | 30% |