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Ideas for how informaticians can get involved with COVID-19 research

Overview of attention for article published in BioData Mining, May 2020
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#12 of 320)
  • High Attention Score compared to outputs of the same age (91st percentile)

Mentioned by

blogs
1 blog
twitter
43 X users

Citations

dimensions_citation
22 Dimensions

Readers on

mendeley
217 Mendeley
Title
Ideas for how informaticians can get involved with COVID-19 research
Published in
BioData Mining, May 2020
DOI 10.1186/s13040-020-00213-y
Pubmed ID
Authors

Jason H. Moore, Ian Barnett, Mary Regina Boland, Yong Chen, George Demiris, Graciela Gonzalez-Hernandez, Daniel S. Herman, Blanca E. Himes, Rebecca A. Hubbard, Dokyoon Kim, Jeffrey S. Morris, Danielle L. Mowery, Marylyn D. Ritchie, Li Shen, Ryan Urbanowicz, John H. Holmes

X Demographics

X Demographics

The data shown below were collected from the profiles of 43 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 217 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 217 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 28 13%
Researcher 19 9%
Student > Ph. D. Student 18 8%
Student > Bachelor 18 8%
Other 10 5%
Other 49 23%
Unknown 75 35%
Readers by discipline Count As %
Medicine and Dentistry 40 18%
Computer Science 21 10%
Social Sciences 11 5%
Biochemistry, Genetics and Molecular Biology 10 5%
Nursing and Health Professions 10 5%
Other 49 23%
Unknown 76 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 33. 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 05 February 2021.
All research outputs
#1,173,671
of 24,974,461 outputs
Outputs from BioData Mining
#12
of 320 outputs
Outputs of similar age
#31,768
of 390,984 outputs
Outputs of similar age from BioData Mining
#2
of 4 outputs
Altmetric has tracked 24,974,461 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 95th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 320 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.5. This one has done particularly well, scoring higher than 96% 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 390,984 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 91% of its contemporaries.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.