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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Local Optima Networks: A New Model of Combinatorial Fitness Landscapes
|
|---|---|
| Chapter number | 9 |
| Book title |
Recent Advances in the Theory and Application of Fitness Landscapes
|
| Published in |
arXiv, January 2014
|
| DOI | 10.1007/978-3-642-41888-4_9 |
| Book ISBNs |
978-3-64-241887-7, 978-3-64-241888-4
|
| Authors |
Gabriela Ochoa, Sébastien Verel, Fabio Daolio, Marco Tomassini |
X Demographics
The data shown below were collected from the profiles of 9 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Belgium | 2 | 22% |
| Germany | 2 | 22% |
| United States | 1 | 11% |
| Norway | 1 | 11% |
| Turkey | 1 | 11% |
| Unknown | 2 | 22% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 44% |
| Scientists | 4 | 44% |
| Science communicators (journalists, bloggers, editors) | 1 | 11% |
Mendeley readers
The data shown below were compiled from readership statistics for 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 4% |
| Japan | 1 | 2% |
| Unknown | 44 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 15 | 32% |
| Researcher | 8 | 17% |
| Student > Bachelor | 7 | 15% |
| Student > Master | 4 | 9% |
| Professor | 3 | 6% |
| Other | 7 | 15% |
| Unknown | 3 | 6% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 27 | 57% |
| Physics and Astronomy | 5 | 11% |
| Biochemistry, Genetics and Molecular Biology | 3 | 6% |
| Social Sciences | 2 | 4% |
| Engineering | 2 | 4% |
| Other | 3 | 6% |
| Unknown | 5 | 11% |
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 27 October 2020.
All research outputs
#4,643,568
of 22,743,667 outputs
Outputs from arXiv
#105,098
of 933,389 outputs
Outputs of similar age
#56,432
of 305,223 outputs
Outputs of similar age from arXiv
#560
of 9,916 outputs
Altmetric has tracked 22,743,667 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 933,389 research outputs from this source. They receive a mean Attention Score of 3.9. This one has done well, scoring higher than 88% 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 305,223 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 81% of its contemporaries.
We're also able to compare this research output to 9,916 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 94% of its contemporaries.