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Audio-Visual Emotion Recognition Using Big Data Towards 5G

Overview of attention for article published in Mobile Networks and Applications, January 2016
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#16 of 327)
  • High Attention Score compared to outputs of the same age (85th percentile)

Mentioned by

news
1 news outlet

Citations

dimensions_citation
73 Dimensions

Readers on

mendeley
77 Mendeley
Title
Audio-Visual Emotion Recognition Using Big Data Towards 5G
Published in
Mobile Networks and Applications, January 2016
DOI 10.1007/s11036-016-0685-9
Authors

M. Shamim Hossain, Ghulam Muhammad, Mohammed F. Alhamid, Biao Song, Khaled Al-Mutib

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 77 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 1%
Unknown 76 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 16 21%
Student > Master 11 14%
Student > Bachelor 9 12%
Professor 7 9%
Researcher 6 8%
Other 9 12%
Unknown 19 25%
Readers by discipline Count As %
Computer Science 25 32%
Engineering 15 19%
Business, Management and Accounting 4 5%
Arts and Humanities 3 4%
Social Sciences 2 3%
Other 5 6%
Unknown 23 30%
Attention Score in Context

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 09 September 2016.
All research outputs
#2,952,681
of 22,886,568 outputs
Outputs from Mobile Networks and Applications
#16
of 327 outputs
Outputs of similar age
#54,533
of 396,828 outputs
Outputs of similar age from Mobile Networks and Applications
#1
of 3 outputs
Altmetric has tracked 22,886,568 research outputs across all sources so far. Compared to these this one has done well and is in the 86th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 327 research outputs from this source. They receive a mean Attention Score of 4.2. This one has done particularly well, scoring higher than 95% 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 396,828 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 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