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Mobility network models of COVID-19 explain inequities and inform reopening

Overview of attention for article published in Nature, November 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 (#11 of 100,408)
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

news
388 news outlets
blogs
25 blogs
policy
9 policy sources
twitter
11566 X users
patent
2 patents
facebook
12 Facebook pages
wikipedia
4 Wikipedia pages
reddit
17 Redditors

Citations

dimensions_citation
1234 Dimensions

Readers on

mendeley
1231 Mendeley
Title
Mobility network models of COVID-19 explain inequities and inform reopening
Published in
Nature, November 2020
DOI 10.1038/s41586-020-2923-3
Pubmed ID
Authors

Serina Chang, Emma Pierson, Pang Wei Koh, Jaline Gerardin, Beth Redbird, David Grusky, Jure Leskovec

X Demographics

X Demographics

The data shown below were collected from the profiles of 11,566 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 1,231 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 1231 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 198 16%
Researcher 179 15%
Student > Master 120 10%
Student > Bachelor 64 5%
Other 60 5%
Other 225 18%
Unknown 385 31%
Readers by discipline Count As %
Medicine and Dentistry 106 9%
Computer Science 100 8%
Engineering 81 7%
Social Sciences 71 6%
Agricultural and Biological Sciences 59 5%
Other 350 28%
Unknown 464 38%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 10165. 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 May 2024.
All research outputs
#185
of 26,377,159 outputs
Outputs from Nature
#11
of 100,408 outputs
Outputs of similar age
#14
of 439,392 outputs
Outputs of similar age from Nature
#2
of 901 outputs
Altmetric has tracked 26,377,159 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 100,408 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 103.4. This one has done particularly well, scoring higher than 99% 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 439,392 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 99% of its contemporaries.
We're also able to compare this research output to 901 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 99% of its contemporaries.