You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
| Title |
Maintaining intellectual diversity in data science
|
|---|---|
| Published in |
Data Science, October 2017
|
| DOI | 10.3233/ds-170003 |
| Authors |
Richard P. Mann, Olivia Woolley-Meza |
Twitter Demographics
The data shown below were collected from the profiles of 12 tweeters who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 3 | 25% |
| Netherlands | 2 | 17% |
| United States | 1 | 8% |
| Chile | 1 | 8% |
| Unknown | 5 | 42% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 8 | 67% |
| Scientists | 3 | 25% |
| Science communicators (journalists, bloggers, editors) | 1 | 8% |
Mendeley readers
The data shown below were compiled from readership statistics for 2 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 2 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 1 | 50% |
| Other | 1 | 50% |
| Student > Ph. D. Student | 1 | 50% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 1 | 50% |
| Physics and Astronomy | 1 | 50% |
| Social Sciences | 1 | 50% |