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Predicting bankruptcy of firms using earnings call data and transfer learning

Overview of attention for article published in PeerJ Computer Science, January 2023
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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 (93rd percentile)

Mentioned by

twitter
43 X users
facebook
1 Facebook page

Readers on

mendeley
24 Mendeley
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Title
Predicting bankruptcy of firms using earnings call data and transfer learning
Published in
PeerJ Computer Science, January 2023
DOI 10.7717/peerj-cs.1134
Pubmed ID
Authors

Hafeez Ur Rehman Siddiqui, Beatriz Sainz de Abajo, Isabel de la Torre Díez, Furqan Rustam, Amjad Raza, Sajjad Atta, Imran Ashraf

Timeline

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X Demographics

X Demographics

The data shown below were collected from the profiles of 43 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
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 %
Unspecified 2 8%
Student > Ph. D. Student 2 8%
Lecturer 2 8%
Other 1 4%
Professor 1 4%
Other 1 4%
Unknown 15 63%
Readers by discipline Count As %
Computer Science 4 17%
Economics, Econometrics and Finance 3 13%
Unspecified 2 8%
Business, Management and Accounting 1 4%
Unknown 14 58%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 28. 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 16 January 2024.
All research outputs
#1,423,030
of 25,992,468 outputs
Outputs from PeerJ Computer Science
#1
of 1 outputs
Outputs of similar age
#30,359
of 481,502 outputs
Outputs of similar age from PeerJ Computer Science
#1
of 1 outputs
Altmetric has tracked 25,992,468 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 94th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 27.8. This one scored the same or higher as 0 of them.
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 481,502 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 93% 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