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Twitter Demographics
Mendeley readers
| Title |
Editorial: Machine Learning for Water Resources
|
|---|---|
| Published in |
Frontiers in Artificial Intelligence, May 2021
|
| DOI | 10.3389/frai.2021.699862 |
| Authors |
Gregoire Mariethoz, J. Jaime Gómez-Hernández |
Twitter Demographics
The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 33% |
| Unknown | 2 | 67% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 3 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 9 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 2 | 22% |
| Student > Bachelor | 1 | 11% |
| Lecturer | 1 | 11% |
| Student > Master | 1 | 11% |
| Researcher | 1 | 11% |
| Other | 0 | 0% |
| Unknown | 3 | 33% |
| Readers by discipline | Count | As % |
|---|---|---|
| Engineering | 3 | 33% |
| Agricultural and Biological Sciences | 1 | 11% |
| Materials Science | 1 | 11% |
| Earth and Planetary Sciences | 1 | 11% |
| Unknown | 3 | 33% |