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Mendeley readers
| Chapter title |
Using Computational Intelligence for Tracking COVID-19 Outbreak in Online Social Networks
|
|---|---|
| Chapter number | 3 |
| Book title |
Computational Intelligence Methods in COVID-19: Surveillance, Prevention, Prediction and Diagnosis
|
| Published by |
Springer, Singapore, October 2020
|
| DOI | 10.1007/978-981-15-8534-0_3 |
| Book ISBNs |
978-9-81-158533-3, 978-9-81-158534-0
|
| Authors |
Sahar Qazi, Salim Ahmad, Khalid Raza, Qazi, Sahar, Ahmad, Salim, Raza, Khalid |
Mendeley readers
The data shown below were compiled from readership statistics for 21 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 21 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 4 | 19% |
| Student > Ph. D. Student | 4 | 19% |
| Lecturer | 2 | 10% |
| Professor > Associate Professor | 2 | 10% |
| Other | 2 | 10% |
| Other | 4 | 19% |
| Unknown | 3 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 6 | 29% |
| Mathematics | 2 | 10% |
| Nursing and Health Professions | 2 | 10% |
| Environmental Science | 1 | 5% |
| Arts and Humanities | 1 | 5% |
| Other | 4 | 19% |
| Unknown | 5 | 24% |