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Characterizing Influenza surveillance systems performance: application of a Bayesian hierarchical statistical model to Hong Kong surveillance data

Overview of attention for article published in BMC Public Health, August 2014
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About this Attention Score

  • Average Attention Score compared to outputs of the same age

Mentioned by

twitter
1 tweeter

Citations

dimensions_citation
8 Dimensions

Readers on

mendeley
59 Mendeley
citeulike
1 CiteULike
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Title
Characterizing Influenza surveillance systems performance: application of a Bayesian hierarchical statistical model to Hong Kong surveillance data
Published in
BMC Public Health, August 2014
DOI 10.1186/1471-2458-14-850
Pubmed ID
Authors

Ying Zhang, Ali Arab, Benjamin J Cowling, Michael A Stoto

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 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 59 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 12 20%
Student > Master 9 15%
Student > Ph. D. Student 9 15%
Student > Bachelor 6 10%
Student > Doctoral Student 4 7%
Other 12 20%
Unknown 7 12%
Readers by discipline Count As %
Medicine and Dentistry 17 29%
Nursing and Health Professions 7 12%
Agricultural and Biological Sciences 6 10%
Social Sciences 4 7%
Computer Science 3 5%
Other 11 19%
Unknown 11 19%

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 12 March 2020.
All research outputs
#11,249,407
of 17,379,776 outputs
Outputs from BMC Public Health
#8,954
of 11,743 outputs
Outputs of similar age
#162,768
of 270,321 outputs
Outputs of similar age from BMC Public Health
#1
of 1 outputs
Altmetric has tracked 17,379,776 research outputs across all sources so far. This one is in the 23rd percentile – i.e., 23% of other outputs scored the same or lower than it.
So far Altmetric has tracked 11,743 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.4. This one is in the 16th percentile – i.e., 16% 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 270,321 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.
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