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Estimating direct and spill-over impacts of political elections on COVID-19 transmission using synthetic control methods

Overview of attention for article published in PLoS Computational Biology, May 2021
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (98th percentile)
  • High Attention Score compared to outputs of the same age and source (98th percentile)

Mentioned by

news
7 news outlets
blogs
1 blog
twitter
183 X users
facebook
1 Facebook page
reddit
2 Redditors

Citations

dimensions_citation
30 Dimensions

Readers on

mendeley
76 Mendeley
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Title
Estimating direct and spill-over impacts of political elections on COVID-19 transmission using synthetic control methods
Published in
PLoS Computational Biology, May 2021
DOI 10.1371/journal.pcbi.1008959
Pubmed ID
Authors

Jue Tao Lim, Kenwin Maung, Sok Teng Tan, Suan Ee Ong, Jane Mingjie Lim, Joel Ruihan Koo, Haoyang Sun, Minah Park, Ken Wei Tan, Joanne Yoong, Alex R. Cook, Borame Sue Lee Dickens

Timeline

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X Demographics

X Demographics

The data shown below were collected from the profiles of 183 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 76 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 76 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 11 14%
Researcher 9 12%
Student > Bachelor 5 7%
Student > Postgraduate 4 5%
Lecturer 3 4%
Other 13 17%
Unknown 31 41%
Readers by discipline Count As %
Nursing and Health Professions 5 7%
Medicine and Dentistry 5 7%
Social Sciences 4 5%
Economics, Econometrics and Finance 4 5%
Agricultural and Biological Sciences 3 4%
Other 19 25%
Unknown 36 47%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 205. 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 17 November 2022.
All research outputs
#207,998
of 26,807,699 outputs
Outputs from PLoS Computational Biology
#132
of 9,256 outputs
Outputs of similar age
#5,856
of 466,673 outputs
Outputs of similar age from PLoS Computational Biology
#3
of 209 outputs
Altmetric has tracked 26,807,699 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 9,256 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 20.1. This one has done particularly well, scoring higher than 98% 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 466,673 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 98% of its contemporaries.
We're also able to compare this research output to 209 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 98% of its contemporaries.