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Timeline
X Demographics
Mendeley readers
Attention Score in Context
Title |
Evolutionary Multi-Criterion Optimization
|
---|---|
Published by |
Lecture notes in computer science, January 2017
|
DOI | 10.1007/978-3-319-54157-0 |
ISBNs |
978-3-31-954156-3, 978-3-31-954157-0
|
Editors |
Heike Trautmann, Günter Rudolph, Kathrin Klamroth, Oliver Schütze, Margaret Wiecek, Yaochu Jin, Christian Grimme |
X Demographics
The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Geographical breakdown
Country | Count | As % |
---|---|---|
Spain | 2 | 25% |
Ecuador | 1 | 13% |
Unknown | 5 | 63% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 4 | 50% |
Practitioners (doctors, other healthcare professionals) | 2 | 25% |
Scientists | 1 | 13% |
Science communicators (journalists, bloggers, editors) | 1 | 13% |
Mendeley readers
The data shown below were compiled from readership statistics for 14 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 14 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 3 | 21% |
Student > Master | 2 | 14% |
Professor | 2 | 14% |
Researcher | 2 | 14% |
Student > Bachelor | 1 | 7% |
Other | 1 | 7% |
Unknown | 3 | 21% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 4 | 29% |
Engineering | 2 | 14% |
Mathematics | 2 | 14% |
Biochemistry, Genetics and Molecular Biology | 1 | 7% |
Environmental Science | 1 | 7% |
Other | 0 | 0% |
Unknown | 4 | 29% |
Attention Score in Context
This research output has an Altmetric Attention Score of 18. 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 31 December 2019.
All research outputs
#1,809,657
of 23,305,591 outputs
Outputs from Lecture notes in computer science
#309
of 8,162 outputs
Outputs of similar age
#39,369
of 422,802 outputs
Outputs of similar age from Lecture notes in computer science
#13
of 150 outputs
Altmetric has tracked 23,305,591 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 8,162 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.0. This one has done particularly well, scoring higher than 96% 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 422,802 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 90% of its contemporaries.
We're also able to compare this research output to 150 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.