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Coupling effects on turning points of infectious diseases epidemics in scale-free networks

Overview of attention for article published in BMC Bioinformatics, May 2017
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Mentioned by

twitter
1 tweeter

Citations

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1 Dimensions

Readers on

mendeley
5 Mendeley
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Title
Coupling effects on turning points of infectious diseases epidemics in scale-free networks
Published in
BMC Bioinformatics, May 2017
DOI 10.1186/s12859-017-1643-7
Pubmed ID
Authors

Kiseong Kim, Sangyeon Lee, Doheon Lee, Kwang Hyung Lee

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 2 40%
Student > Ph. D. Student 1 20%
Professor > Associate Professor 1 20%
Unknown 1 20%
Readers by discipline Count As %
Unspecified 1 20%
Psychology 1 20%
Economics, Econometrics and Finance 1 20%
Design 1 20%
Unknown 1 20%

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 February 2020.
All research outputs
#13,784,096
of 15,621,958 outputs
Outputs from BMC Bioinformatics
#5,284
of 5,681 outputs
Outputs of similar age
#239,552
of 292,423 outputs
Outputs of similar age from BMC Bioinformatics
#9
of 10 outputs
Altmetric has tracked 15,621,958 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 5,681 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.0. This one is in the 1st percentile – i.e., 1% 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 292,423 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 10 others from the same source and published within six weeks on either side of this one.