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X Demographics
Mendeley readers
Attention Score in Context
Chapter title |
A Neural Network for Semi-Supervised Learning on Manifolds
|
---|---|
Chapter number | 30 |
Book title |
Artificial Neural Networks and Machine Learning – ICANN 2019: Theoretical Neural Computation
|
Published in |
arXiv, August 2019
|
DOI | 10.1007/978-3-030-30487-4_30 |
Book ISBNs |
978-3-03-030486-7, 978-3-03-030487-4
|
Authors |
Alexander Genkin, Anirvan M. Sengupta, Dmitri Chklovskii, Genkin, Alexander, Sengupta, Anirvan M., Chklovskii, Dmitri |
X Demographics
The data shown below were collected from the profiles of 21 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
Australia | 2 | 10% |
United States | 2 | 10% |
Japan | 2 | 10% |
India | 2 | 10% |
Canada | 1 | 5% |
Turkey | 1 | 5% |
France | 1 | 5% |
Unknown | 10 | 48% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 20 | 95% |
Scientists | 1 | 5% |
Mendeley readers
The data shown below were compiled from readership statistics for 37 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 37 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 13 | 35% |
Student > Master | 5 | 14% |
Professor | 2 | 5% |
Researcher | 2 | 5% |
Student > Doctoral Student | 1 | 3% |
Other | 4 | 11% |
Unknown | 10 | 27% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 16 | 43% |
Engineering | 5 | 14% |
Physics and Astronomy | 2 | 5% |
Mathematics | 1 | 3% |
Agricultural and Biological Sciences | 1 | 3% |
Other | 2 | 5% |
Unknown | 10 | 27% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. 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 28 August 2019.
All research outputs
#4,169,675
of 24,998,746 outputs
Outputs from arXiv
#76,132
of 1,020,408 outputs
Outputs of similar age
#76,002
of 347,996 outputs
Outputs of similar age from arXiv
#2,190
of 26,108 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 83rd 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 347,996 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 78% of its contemporaries.
We're also able to compare this research output to 26,108 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 91% of its contemporaries.