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Partisan Differences in Legislators’ Discussion of Vaccination on Twitter During the COVID-19 Era: Natural Language Processing Analysis

Overview of attention for article published in JMIR Infodemiology, February 2022
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#16 of 121)
  • High Attention Score compared to outputs of the same age (88th percentile)
  • Good Attention Score compared to outputs of the same age and source (78th percentile)

Mentioned by

news
1 news outlet
blogs
1 blog
twitter
9 X users
facebook
1 Facebook page
video
1 YouTube creator

Citations

dimensions_citation
7 Dimensions

Readers on

mendeley
26 Mendeley
Title
Partisan Differences in Legislators’ Discussion of Vaccination on Twitter During the COVID-19 Era: Natural Language Processing Analysis
Published in
JMIR Infodemiology, February 2022
DOI 10.2196/32372
Pubmed ID
Authors

Eden Engel-Rebitzer, Daniel C Stokes, Zachary F Meisel, Jonathan Purtle, Rebecca Doyle, Alison M Buttenheim

Timeline
X Demographics

X Demographics

The data shown below were collected from the profiles of 9 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 26 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 26 100%

Demographic breakdown

Readers by professional status Count As %
Lecturer 3 12%
Student > Master 3 12%
Student > Bachelor 2 8%
Professor > Associate Professor 2 8%
Student > Ph. D. Student 1 4%
Other 3 12%
Unknown 12 46%
Readers by discipline Count As %
Social Sciences 5 19%
Business, Management and Accounting 2 8%
Biochemistry, Genetics and Molecular Biology 1 4%
Agricultural and Biological Sciences 1 4%
Nursing and Health Professions 1 4%
Other 2 8%
Unknown 14 54%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 16. 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 08 December 2022.
All research outputs
#2,225,009
of 24,969,131 outputs
Outputs from JMIR Infodemiology
#16
of 121 outputs
Outputs of similar age
#51,752
of 436,113 outputs
Outputs of similar age from JMIR Infodemiology
#4
of 14 outputs
Altmetric has tracked 24,969,131 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 121 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.7. This one has done well, scoring higher than 87% 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 436,113 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 88% of its contemporaries.
We're also able to compare this research output to 14 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 78% of its contemporaries.