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Mining a stroke knowledge graph from literature

Overview of attention for article published in BMC Bioinformatics, July 2021
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About this Attention Score

  • Average Attention Score compared to outputs of the same age

Mentioned by

twitter
4 X users

Citations

dimensions_citation
7 Dimensions

Readers on

mendeley
45 Mendeley
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Title
Mining a stroke knowledge graph from literature
Published in
BMC Bioinformatics, July 2021
DOI 10.1186/s12859-021-04292-4
Pubmed ID
Authors

Xi Yang, Chengkun Wu, Goran Nenadic, Wei Wang, Kai Lu

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 45 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 11%
Student > Bachelor 4 9%
Researcher 3 7%
Student > Doctoral Student 3 7%
Professor > Associate Professor 2 4%
Other 7 16%
Unknown 21 47%
Readers by discipline Count As %
Computer Science 9 20%
Agricultural and Biological Sciences 4 9%
Biochemistry, Genetics and Molecular Biology 3 7%
Business, Management and Accounting 2 4%
Unspecified 1 2%
Other 2 4%
Unknown 24 53%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 30 July 2021.
All research outputs
#15,329,366
of 23,577,761 outputs
Outputs from BMC Bioinformatics
#5,159
of 7,418 outputs
Outputs of similar age
#236,210
of 435,338 outputs
Outputs of similar age from BMC Bioinformatics
#96
of 111 outputs
Altmetric has tracked 23,577,761 research outputs across all sources so far. This one is in the 32nd percentile – i.e., 32% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,418 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 26th percentile – i.e., 26% of its peers scored the same or lower than it.
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 435,338 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 111 others from the same source and published within six weeks on either side of this one. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.