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X Demographics
Mendeley readers
Attention Score in Context
Title |
Ten Simple Rules for the Open Development of Scientific Software
|
---|---|
Published in |
PLoS Computational Biology, December 2012
|
DOI | 10.1371/journal.pcbi.1002802 |
Pubmed ID | |
Authors |
Andreas Prlić, James B. Procter |
X Demographics
The data shown below were collected from the profiles of 251 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 | 44 | 18% |
United Kingdom | 23 | 9% |
Spain | 19 | 8% |
France | 12 | 5% |
Japan | 7 | 3% |
Brazil | 7 | 3% |
Australia | 5 | 2% |
Venezuela, Bolivarian Republic of | 5 | 2% |
Italy | 5 | 2% |
Other | 48 | 19% |
Unknown | 76 | 30% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 165 | 66% |
Scientists | 75 | 30% |
Science communicators (journalists, bloggers, editors) | 9 | 4% |
Practitioners (doctors, other healthcare professionals) | 2 | <1% |
Mendeley readers
The data shown below were compiled from readership statistics for 509 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 23 | 5% |
United Kingdom | 11 | 2% |
France | 7 | 1% |
Spain | 7 | 1% |
Germany | 6 | 1% |
Netherlands | 6 | 1% |
Brazil | 4 | <1% |
Belgium | 3 | <1% |
Ireland | 2 | <1% |
Other | 33 | 6% |
Unknown | 407 | 80% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 150 | 29% |
Student > Ph. D. Student | 129 | 25% |
Student > Master | 43 | 8% |
Other | 32 | 6% |
Professor > Associate Professor | 26 | 5% |
Other | 85 | 17% |
Unknown | 44 | 9% |
Readers by discipline | Count | As % |
---|---|---|
Agricultural and Biological Sciences | 186 | 37% |
Computer Science | 65 | 13% |
Biochemistry, Genetics and Molecular Biology | 42 | 8% |
Engineering | 23 | 5% |
Medicine and Dentistry | 21 | 4% |
Other | 114 | 22% |
Unknown | 58 | 11% |
Attention Score in Context
This research output has an Altmetric Attention Score of 229. 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 30 August 2022.
All research outputs
#170,816
of 25,850,671 outputs
Outputs from PLoS Computational Biology
#114
of 9,054 outputs
Outputs of similar age
#957
of 289,051 outputs
Outputs of similar age from PLoS Computational Biology
#2
of 131 outputs
Altmetric has tracked 25,850,671 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,054 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.3. This one has done particularly well, scoring higher than 98% 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 289,051 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 99% of its contemporaries.
We're also able to compare this research output to 131 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 98% of its contemporaries.