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X Demographics
Mendeley readers
Attention Score in Context
| 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 |
X Demographics
The data shown below were collected from the profiles of 115 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| India | 23 | 20% |
| United Kingdom | 13 | 11% |
| United States | 5 | 4% |
| Australia | 3 | 3% |
| Canada | 2 | 2% |
| Turkey | 2 | 2% |
| Cuba | 2 | 2% |
| Mauritius | 2 | 2% |
| Switzerland | 2 | 2% |
| Other | 19 | 17% |
| Unknown | 42 | 37% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 104 | 90% |
| Scientists | 9 | 8% |
| Science communicators (journalists, bloggers, editors) | 1 | <1% |
| Practitioners (doctors, other healthcare professionals) | 1 | <1% |
Mendeley readers
The data shown below were compiled from readership statistics for 375 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 375 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 33 | 9% |
| Researcher | 31 | 8% |
| Student > Ph. D. Student | 30 | 8% |
| Lecturer | 27 | 7% |
| Student > Doctoral Student | 22 | 6% |
| Other | 74 | 20% |
| Unknown | 158 | 42% |
| Readers by discipline | Count | As % |
|---|---|---|
| Social Sciences | 34 | 9% |
| Medicine and Dentistry | 33 | 9% |
| Computer Science | 20 | 5% |
| Business, Management and Accounting | 18 | 5% |
| Economics, Econometrics and Finance | 12 | 3% |
| Other | 81 | 22% |
| Unknown | 177 | 47% |
Attention Score in Context
This research output has an Altmetric Attention Score of 295. 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
#120,501
of 25,775,807 outputs
Outputs from PLOS ONE
#1,881
of 224,662 outputs
Outputs of similar age
#3,747
of 427,510 outputs
Outputs of similar age from PLOS ONE
#36
of 2,876 outputs
Altmetric has tracked 25,775,807 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 224,662 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.8. 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 427,510 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 2,876 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.