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X Demographics
Mendeley readers
Attention Score in Context
| Title |
Googling Food Webs: Can an Eigenvector Measure Species' Importance for Coextinctions?
|
|---|---|
| Published in |
PLoS Computational Biology, September 2009
|
| DOI | 10.1371/journal.pcbi.1000494 |
| Pubmed ID | |
| Authors |
Stefano Allesina, Mercedes Pascual |
X Demographics
The data shown below were collected from the profiles of 6 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Portugal | 1 | 17% |
| France | 1 | 17% |
| Argentina | 1 | 17% |
| Unknown | 3 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 83% |
| Science communicators (journalists, bloggers, editors) | 1 | 17% |
| Scientists | 1 | 17% |
Mendeley readers
The data shown below were compiled from readership statistics for 406 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 26 | 6% |
| Switzerland | 5 | 1% |
| United Kingdom | 4 | <1% |
| Germany | 3 | <1% |
| Netherlands | 3 | <1% |
| France | 3 | <1% |
| Canada | 3 | <1% |
| Norway | 2 | <1% |
| Sweden | 2 | <1% |
| Other | 16 | 4% |
| Unknown | 339 | 83% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 105 | 26% |
| Student > Ph. D. Student | 97 | 24% |
| Professor > Associate Professor | 31 | 8% |
| Student > Master | 30 | 7% |
| Student > Doctoral Student | 24 | 6% |
| Other | 84 | 21% |
| Unknown | 35 | 9% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 171 | 42% |
| Environmental Science | 84 | 21% |
| Computer Science | 20 | 5% |
| Physics and Astronomy | 17 | 4% |
| Mathematics | 13 | 3% |
| Other | 58 | 14% |
| Unknown | 43 | 11% |
Attention Score in Context
This research output has an Altmetric Attention Score of 42. 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 02 November 2021.
All research outputs
#980,817
of 25,483,400 outputs
Outputs from PLoS Computational Biology
#746
of 8,986 outputs
Outputs of similar age
#2,540
of 102,877 outputs
Outputs of similar age from PLoS Computational Biology
#5
of 50 outputs
Altmetric has tracked 25,483,400 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 96th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,986 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.4. This one has done particularly well, scoring higher than 91% 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 102,877 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 97% of its contemporaries.
We're also able to compare this research output to 50 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 92% of its contemporaries.