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Article Metrics

India nudges to contain COVID-19 pandemic: A reactive public policy analysis using machine-learning based topic modelling

Overview of attention for article published in PLoS ONE, September 2020
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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 (99th percentile)
  • High Attention Score compared to outputs of the same age and source (95th percentile)

Mentioned by

news
25 news outlets
blogs
1 blog
twitter
116 tweeters
facebook
1 Facebook page

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
52 Mendeley
Title
India nudges to contain COVID-19 pandemic: A reactive public policy analysis using machine-learning based topic modelling
Published in
PLoS ONE, September 2020
DOI 10.1371/journal.pone.0238972
Pubmed ID
Authors

Ramit Debnath, Ronita Bardhan

Twitter Demographics

The data shown below were collected from the profiles of 116 tweeters 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 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 52 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 10 19%
Other 7 13%
Student > Bachelor 5 10%
Lecturer 4 8%
Student > Ph. D. Student 3 6%
Other 12 23%
Unknown 11 21%
Readers by discipline Count As %
Medicine and Dentistry 9 17%
Engineering 4 8%
Social Sciences 4 8%
Computer Science 4 8%
Nursing and Health Professions 4 8%
Other 12 23%
Unknown 15 29%

Attention Score in Context

This research output has an Altmetric Attention Score of 294. 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 22 November 2020.
All research outputs
#57,743
of 16,275,632 outputs
Outputs from PLoS ONE
#1,088
of 159,442 outputs
Outputs of similar age
#2,521
of 305,865 outputs
Outputs of similar age from PLoS ONE
#12
of 279 outputs
Altmetric has tracked 16,275,632 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 159,442 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.1. 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 305,865 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 279 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 95% of its contemporaries.