| Title |
Exposing the probabilistic causal structure of discrimination
|
|---|---|
| Published in |
International Journal of Data Science and Analytics, January 2017
|
| DOI | 10.1007/s41060-016-0040-z |
| Authors |
Francesco Bonchi, Sara Hajian, Bud Mishra, Daniele Ramazzotti |
X Demographics
The data shown below were collected from the profiles of 13 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 15% |
| Germany | 1 | 8% |
| Côte d'Ivoire | 1 | 8% |
| Italy | 1 | 8% |
| United Kingdom | 1 | 8% |
| Canada | 1 | 8% |
| Portugal | 1 | 8% |
| Unknown | 5 | 38% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 9 | 69% |
| Scientists | 3 | 23% |
| Science communicators (journalists, bloggers, editors) | 1 | 8% |
Mendeley readers
The data shown below were compiled from readership statistics for 171 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 171 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 36 | 21% |
| Student > Ph. D. Student | 35 | 20% |
| Researcher | 16 | 9% |
| Student > Bachelor | 14 | 8% |
| Professor | 6 | 4% |
| Other | 24 | 14% |
| Unknown | 40 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 71 | 42% |
| Engineering | 13 | 8% |
| Social Sciences | 12 | 7% |
| Business, Management and Accounting | 6 | 4% |
| Arts and Humanities | 5 | 3% |
| Other | 16 | 9% |
| Unknown | 48 | 28% |
Attention Score in Context
This research output has an Altmetric Attention Score of 7. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 10 March 2017.
All research outputs
#5,132,740
of 25,377,790 outputs
Outputs from International Journal of Data Science and Analytics
#24
of 253 outputs
Outputs of similar age
#96,481
of 422,539 outputs
Outputs of similar age from International Journal of Data Science and Analytics
#2
of 7 outputs
Altmetric has tracked 25,377,790 research outputs across all sources so far. Compared to these this one has done well and is in the 79th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 253 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has done particularly well, scoring higher than 90% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 422,539 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 77% of its contemporaries.
We're also able to compare this research output to 7 others from the same source and published within six weeks on either side of this one. This one has scored higher than 5 of them.