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COVID-19 information retrieval with deep-learning based semantic search, question answering, and abstractive summarization

Overview of attention for article published in npj Digital Medicine, April 2021
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (82nd percentile)

Mentioned by

blogs
1 blog
twitter
8 tweeters

Citations

dimensions_citation
10 Dimensions

Readers on

mendeley
77 Mendeley
Title
COVID-19 information retrieval with deep-learning based semantic search, question answering, and abstractive summarization
Published in
npj Digital Medicine, April 2021
DOI 10.1038/s41746-021-00437-0
Pubmed ID
Authors

Andre Esteva, Anuprit Kale, Romain Paulus, Kazuma Hashimoto, Wenpeng Yin, Dragomir Radev, Richard Socher

Twitter Demographics

The data shown below were collected from the profiles of 8 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 77 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 77 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 11 14%
Researcher 11 14%
Student > Bachelor 7 9%
Student > Ph. D. Student 7 9%
Lecturer 5 6%
Other 15 19%
Unknown 21 27%
Readers by discipline Count As %
Computer Science 35 45%
Medicine and Dentistry 4 5%
Agricultural and Biological Sciences 3 4%
Social Sciences 3 4%
Business, Management and Accounting 2 3%
Other 6 8%
Unknown 24 31%

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 13 April 2021.
All research outputs
#2,181,382
of 18,209,496 outputs
Outputs from npj Digital Medicine
#311
of 452 outputs
Outputs of similar age
#57,299
of 327,392 outputs
Outputs of similar age from npj Digital Medicine
#1
of 1 outputs
Altmetric has tracked 18,209,496 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 452 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 64.0. This one is in the 31st percentile – i.e., 31% of its peers scored the same or lower than it.
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 327,392 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 82% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them