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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
6 Dimensions

Readers on

mendeley
24 Mendeley
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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

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 24 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 24 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 13%
Lecturer 2 8%
Student > Bachelor 2 8%
Professor > Associate Professor 2 8%
Student > Ph. D. Student 1 4%
Other 2 8%
Unknown 12 50%
Readers by discipline Count As %
Social Sciences 5 21%
Biochemistry, Genetics and Molecular Biology 1 4%
Business, Management and Accounting 1 4%
Agricultural and Biological Sciences 1 4%
Nursing and Health Professions 1 4%
Other 2 8%
Unknown 13 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.