| Title |
Gerrymandering and computational redistricting
|
|---|---|
| Published in |
Journal of Computational Social Science, August 2019
|
| DOI | 10.1007/s42001-019-00053-9 |
| Pubmed ID | |
| Authors |
Olivia Guest, Frank J. Kanayet, Bradley C. Love |
X Demographics
The data shown below were collected from the profiles of 196 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 | 63 | 32% |
| United Kingdom | 34 | 17% |
| Canada | 5 | 3% |
| Netherlands | 4 | 2% |
| Germany | 4 | 2% |
| Portugal | 2 | 1% |
| Ireland | 2 | 1% |
| Austria | 1 | <1% |
| Italy | 1 | <1% |
| Other | 7 | 4% |
| Unknown | 73 | 37% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 124 | 63% |
| Scientists | 66 | 34% |
| Science communicators (journalists, bloggers, editors) | 3 | 2% |
| Practitioners (doctors, other healthcare professionals) | 2 | 1% |
| Unknown | 1 | <1% |
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 | 5 | 24% |
| Student > Ph. D. Student | 3 | 14% |
| Student > Doctoral Student | 2 | 10% |
| Student > Master | 1 | 5% |
| Lecturer | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 9 | 43% |
| Readers by discipline | Count | As % |
|---|---|---|
| Social Sciences | 7 | 33% |
| Engineering | 2 | 10% |
| Neuroscience | 1 | 5% |
| Psychology | 1 | 5% |
| Unknown | 10 | 48% |
Attention Score in Context
This research output has an Altmetric Attention Score of 130. 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 26 October 2023.
All research outputs
#324,139
of 25,706,302 outputs
Outputs from Journal of Computational Social Science
#7
of 150 outputs
Outputs of similar age
#6,371
of 354,852 outputs
Outputs of similar age from Journal of Computational Social Science
#1
of 7 outputs
Altmetric has tracked 25,706,302 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 150 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 30.3. This one has done particularly well, scoring higher than 95% 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 354,852 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 98% 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 all of them