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X Demographics
Mendeley readers
Attention Score in Context
Title |
Two-Level Domain Adaptation Neural Network for EEG-Based Emotion Recognition
|
---|---|
Published in |
Frontiers in Human Neuroscience, January 2021
|
DOI | 10.3389/fnhum.2020.605246 |
Pubmed ID | |
Authors |
Guangcheng Bao, Ning Zhuang, Li Tong, Bin Yan, Jun Shu, Linyuan Wang, Ying Zeng, Zhichong Shen |
X Demographics
The data shown below were collected from the profiles of 33 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 4 | 12% |
Brazil | 2 | 6% |
Kenya | 2 | 6% |
Comoros | 1 | 3% |
United Kingdom | 1 | 3% |
India | 1 | 3% |
Cameroon | 1 | 3% |
Switzerland | 1 | 3% |
Sri Lanka | 1 | 3% |
Other | 1 | 3% |
Unknown | 18 | 55% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 31 | 94% |
Scientists | 2 | 6% |
Mendeley readers
The data shown below were compiled from readership statistics for 43 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 43 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Master | 8 | 19% |
Student > Ph. D. Student | 7 | 16% |
Student > Postgraduate | 2 | 5% |
Student > Doctoral Student | 1 | 2% |
Lecturer > Senior Lecturer | 1 | 2% |
Other | 2 | 5% |
Unknown | 22 | 51% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 8 | 19% |
Engineering | 7 | 16% |
Psychology | 2 | 5% |
Social Sciences | 1 | 2% |
Business, Management and Accounting | 1 | 2% |
Other | 2 | 5% |
Unknown | 22 | 51% |
Attention Score in Context
This research output has an Altmetric Attention Score of 13. 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 07 February 2021.
All research outputs
#2,725,727
of 25,436,226 outputs
Outputs from Frontiers in Human Neuroscience
#1,276
of 7,699 outputs
Outputs of similar age
#74,381
of 523,895 outputs
Outputs of similar age from Frontiers in Human Neuroscience
#19
of 169 outputs
Altmetric has tracked 25,436,226 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 7,699 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.9. This one has done well, scoring higher than 83% 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 523,895 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 85% of its contemporaries.
We're also able to compare this research output to 169 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.