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.
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X Demographics
Mendeley readers
Attention Score in Context
| Title |
What Can Computational Models Learn From Human Selective Attention? A Review From an Audiovisual Unimodal and Crossmodal Perspective
|
|---|---|
| Published in |
Frontiers in Integrative Neuroscience, February 2020
|
| DOI | 10.3389/fnint.2020.00010 |
| Pubmed ID | |
| Authors |
Di Fu, Cornelius Weber, Guochun Yang, Matthias Kerzel, Weizhi Nan, Pablo Barros, Haiyan Wu, Xun Liu, Stefan Wermter |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 13% |
| Unknown | 7 | 88% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 63% |
| Scientists | 3 | 38% |
Mendeley readers
The data shown below were compiled from readership statistics for 93 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 93 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 18 | 19% |
| Student > Master | 12 | 13% |
| Researcher | 7 | 8% |
| Student > Doctoral Student | 6 | 6% |
| Lecturer | 4 | 4% |
| Other | 12 | 13% |
| Unknown | 34 | 37% |
| Readers by discipline | Count | As % |
|---|---|---|
| Psychology | 14 | 15% |
| Computer Science | 12 | 13% |
| Neuroscience | 10 | 11% |
| Engineering | 6 | 6% |
| Nursing and Health Professions | 4 | 4% |
| Other | 11 | 12% |
| Unknown | 36 | 39% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 17 April 2020.
All research outputs
#7,336,148
of 25,904,557 outputs
Outputs from Frontiers in Integrative Neuroscience
#303
of 920 outputs
Outputs of similar age
#131,231
of 385,920 outputs
Outputs of similar age from Frontiers in Integrative Neuroscience
#10
of 22 outputs
Altmetric has tracked 25,904,557 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 920 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.9. This one has gotten more attention than average, scoring higher than 66% 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 385,920 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 65% of its contemporaries.
We're also able to compare this research output to 22 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 54% of its contemporaries.