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X Demographics
Mendeley readers
Attention Score in Context
| Title |
EEG-Based Emotion Classification Using a Deep Neural Network and Sparse Autoencoder
|
|---|---|
| Published in |
Frontiers in Systems Neuroscience, September 2020
|
| DOI | 10.3389/fnsys.2020.00043 |
| Pubmed ID | |
| Authors |
Junxiu Liu, Guopei Wu, Yuling Luo, Senhui Qiu, Su Yang, Wei Li, Yifei Bi |
X Demographics
The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Finland | 1 | 14% |
| Switzerland | 1 | 14% |
| Unknown | 5 | 71% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 6 | 86% |
| Scientists | 1 | 14% |
Mendeley readers
The data shown below were compiled from readership statistics for 178 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 178 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 26 | 15% |
| Student > Master | 14 | 8% |
| Researcher | 13 | 7% |
| Student > Bachelor | 12 | 7% |
| Other | 4 | 2% |
| Other | 17 | 10% |
| Unknown | 92 | 52% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 38 | 21% |
| Engineering | 21 | 12% |
| Neuroscience | 8 | 4% |
| Unspecified | 5 | 3% |
| Physics and Astronomy | 2 | 1% |
| Other | 12 | 7% |
| Unknown | 92 | 52% |
Attention Score in Context
This research output has an Altmetric Attention Score of 14. 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 02 June 2021.
All research outputs
#2,475,549
of 23,567,572 outputs
Outputs from Frontiers in Systems Neuroscience
#216
of 1,363 outputs
Outputs of similar age
#66,323
of 401,085 outputs
Outputs of similar age from Frontiers in Systems Neuroscience
#13
of 30 outputs
Altmetric has tracked 23,567,572 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,363 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.9. This one has done well, scoring higher than 84% 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 401,085 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 83% of its contemporaries.
We're also able to compare this research output to 30 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 56% of its contemporaries.