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Prediction of bank transaction fraud using TabNet—an adaptive deep learning architecture

Overview of attention for article published in International Review of Economics & Finance, March 2026
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Mentioned by

bluesky
1 Bluesky user

Readers on

mendeley
124 Mendeley
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Article details
Title
Prediction of bank transaction fraud using TabNet—an adaptive deep learning architecture
Published in
International Review of Economics & Finance, March 2026
DOI 10.1016/j.iref.2026.104916
Authors

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Timeline Attention over time Attention Score history
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Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 124 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 124 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Unspecified 17 14%
Other 3 2%
Student > Ph. D. Student 3 2%
Researcher 3 2%
Lecturer > Senior Lecturer 2 2%
Other 8 6%
Unknown 88 71%
Readers by discipline
Readers by discipline Count As %
Unspecified 17 14%
Business, Management and Accounting 7 6%
Computer Science 6 5%
Engineering 5 4%
Immunology and Microbiology 1 <1%
Other 0 0%
Unknown 88 71%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 July 2026.
All research outputs
#27,417,122
of 33,205,760 outputs
Outputs from International Review of Economics & Finance
#573
of 780 outputs
Outputs of similar age
#246,508
of 354,906 outputs
Outputs of similar age from International Review of Economics & Finance
#10
of 12 outputs
Altmetric has tracked 33,205,760 research outputs across all sources so far. This one is in the 9th percentile – i.e., 9% of other outputs scored the same or lower than it.
So far Altmetric has tracked 780 research outputs from this source. They receive a mean Attention Score of 4.3. This one is in the 13th percentile – i.e., 13% 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 354,906 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 12 others from the same source and published within six weeks on either side of this one. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.