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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Massive Multi-agent Data-Driven Simulations of the GitHub Ecosystem
|
|---|---|
| Chapter number | 1 |
| Book title |
Advances in Practical Applications of Survivable Agents and Multi-Agent Systems: The PAAMS Collection
|
| Published in |
arXiv, June 2019
|
| DOI | 10.1007/978-3-030-24209-1_1 |
| Book ISBNs |
978-3-03-024208-4, 978-3-03-024209-1
|
| Authors |
Jim Blythe, John Bollenbacher, Di Huang, Pik-Mai Hui, Rachel Krohn, Diogo Pacheco, Goran Muric, Anna Sapienza, Alexey Tregubov, Yong-Yeol Ahn, Alessandro Flammini, Kristina Lerman, Filippo Menczer, Tim Weninger, Emilio Ferrara, Blythe, Jim, Bollenbacher, John, Huang, Di, Hui, Pik-Mai, Krohn, Rachel, Pacheco, Diogo, Muric, Goran, Sapienza, Anna, Tregubov, Alexey, Ahn, Yong-Yeol, Flammini, Alessandro, Lerman, Kristina, Menczer, Filippo, Weninger, Tim, Ferrara, Emilio |
X Demographics
The data shown below were collected from the profiles of 17 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 | 3 | 18% |
| Canada | 1 | 6% |
| Italy | 1 | 6% |
| Bangladesh | 1 | 6% |
| Ecuador | 1 | 6% |
| Spain | 1 | 6% |
| Unknown | 9 | 53% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 10 | 59% |
| Scientists | 7 | 41% |
Mendeley readers
The data shown below were compiled from readership statistics for 29 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 29 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 5 | 17% |
| Student > Ph. D. Student | 5 | 17% |
| Professor | 3 | 10% |
| Professor > Associate Professor | 3 | 10% |
| Researcher | 3 | 10% |
| Other | 4 | 14% |
| Unknown | 6 | 21% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 15 | 52% |
| Engineering | 5 | 17% |
| Business, Management and Accounting | 1 | 3% |
| Energy | 1 | 3% |
| Biochemistry, Genetics and Molecular Biology | 1 | 3% |
| Other | 0 | 0% |
| Unknown | 6 | 21% |
Attention Score in Context
This research output has an Altmetric Attention Score of 8. 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 22 September 2020.
All research outputs
#4,414,035
of 24,998,746 outputs
Outputs from arXiv
#80,221
of 1,020,408 outputs
Outputs of similar age
#80,727
of 356,797 outputs
Outputs of similar age from arXiv
#2,483
of 26,587 outputs
Altmetric has tracked 24,998,746 research outputs across all sources so far. Compared to these this one has done well and is in the 82nd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,020,408 research outputs from this source. They receive a mean Attention Score of 4.1. This one has done particularly well, scoring higher than 92% 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 356,797 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 26,587 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 90% of its contemporaries.