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The use of data science for education: The case of social-emotional learning

Overview of attention for article published in Smart Learning Environments, January 2017
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (85th percentile)

Mentioned by

twitter
17 tweeters

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
68 Mendeley
Title
The use of data science for education: The case of social-emotional learning
Published in
Smart Learning Environments, January 2017
DOI 10.1186/s40561-016-0040-4
Authors

Ming-Chi Liu, Yueh-Min Huang

Twitter Demographics

The data shown below were collected from the profiles of 17 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 68 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Portugal 1 1%
United States 1 1%
Unknown 66 97%

Demographic breakdown

Readers by professional status Count As %
Student > Master 15 22%
Student > Ph. D. Student 14 21%
Unspecified 13 19%
Professor 4 6%
Researcher 4 6%
Other 18 26%
Readers by discipline Count As %
Computer Science 25 37%
Unspecified 16 24%
Social Sciences 15 22%
Business, Management and Accounting 3 4%
Psychology 3 4%
Other 6 9%

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 21 November 2018.
All research outputs
#1,320,063
of 12,968,588 outputs
Outputs from Smart Learning Environments
#5
of 64 outputs
Outputs of similar age
#48,687
of 342,794 outputs
Outputs of similar age from Smart Learning Environments
#1
of 1 outputs
Altmetric has tracked 12,968,588 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 64 research outputs from this source. They receive a mean Attention Score of 3.3. This one has done particularly well, scoring higher than 92% 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 342,794 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 1 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