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

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	32915899
Authors	Ramit Debnath, Ronita Bardhan

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Twitter Demographics

The data shown below were collected from the profiles of 118 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Geographical breakdown

Country	Count	As %
India	27	23%
United Kingdom	14	12%
United States	5	4%
Australia	3	3%
Canada	2	2%
Turkey	2	2%
Cuba	2	2%
Mauritius	2	2%
Switzerland	2	2%
Other	19	16%
Unknown	40	34%

Demographic breakdown

Type	Count	As %
Members of the public	108	92%
Scientists	7	6%
Science communicators (journalists, bloggers, editors)	2	2%
Practitioners (doctors, other healthcare professionals)	1	<1%

Mendeley readers

The data shown below were compiled from readership statistics for 344 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country	Count	As %
Unknown	344	100%

Demographic breakdown

Readers by professional status	Count	As %
Researcher	31	9%
Student > Master	30	9%
Student > Ph. D. Student	27	8%
Lecturer	24	7%
Student > Bachelor	21	6%
Other	82	24%
Unknown	129	38%

Readers by discipline	Count	As %
Social Sciences	33	10%
Medicine and Dentistry	30	9%
Computer Science	22	6%
Business, Management and Accounting	16	5%
Unspecified	12	3%
Other	86	25%
Unknown	145	42%

Attention Score in Context

This research output has an Altmetric Attention Score of 303. 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 September 2022.

All research outputs

#98,563

of 23,380,821 outputs

Outputs from PLOS ONE

#1,570

of 199,906 outputs

Outputs of similar age

#3,358

of 401,943 outputs

Outputs of similar age from PLOS ONE

#33

of 2,848 outputs

Altmetric has tracked 23,380,821 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 199,906 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.3. 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 401,943 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 2,848 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.

University of Cambridge

Article Metrics

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

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Geographical breakdown

Demographic breakdown

Mendeley readers

Geographical breakdown

Demographic breakdown

Attention Score in Context