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X Demographics
Mendeley readers
Attention Score in Context
| Title |
SORN: A Self-Organizing Recurrent Neural Network
|
|---|---|
| Published in |
Frontiers in Computational Neuroscience, October 2009
|
| DOI | 10.3389/neuro.10.023.2009 |
| Pubmed ID | |
| Authors |
Andreea Lazar, Gordon Pipa, Jochen Triesch |
X Demographics
The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 33% |
| Australia | 1 | 33% |
| United States | 1 | 33% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 67% |
| Scientists | 1 | 33% |
Mendeley readers
The data shown below were compiled from readership statistics for 425 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Germany | 19 | 4% |
| United States | 10 | 2% |
| United Kingdom | 7 | 2% |
| Switzerland | 3 | <1% |
| Portugal | 3 | <1% |
| France | 3 | <1% |
| Japan | 3 | <1% |
| Netherlands | 2 | <1% |
| Canada | 2 | <1% |
| Other | 10 | 2% |
| Unknown | 363 | 85% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 134 | 32% |
| Researcher | 82 | 19% |
| Student > Master | 60 | 14% |
| Student > Bachelor | 40 | 9% |
| Student > Doctoral Student | 28 | 7% |
| Other | 56 | 13% |
| Unknown | 25 | 6% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 119 | 28% |
| Agricultural and Biological Sciences | 72 | 17% |
| Neuroscience | 60 | 14% |
| Engineering | 44 | 10% |
| Physics and Astronomy | 39 | 9% |
| Other | 61 | 14% |
| Unknown | 30 | 7% |
Attention Score in Context
This research output has an Altmetric Attention Score of 10. 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 13 November 2021.
All research outputs
#3,779,343
of 25,374,647 outputs
Outputs from Frontiers in Computational Neuroscience
#175
of 1,463 outputs
Outputs of similar age
#13,670
of 108,320 outputs
Outputs of similar age from Frontiers in Computational Neuroscience
#1
of 3 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. Compared to these this one has done well and is in the 85th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,463 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.0. 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 108,320 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 87% of its contemporaries.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them