↓ Skip to main content

Exploring explainable AI in the tax domain

Overview of attention for article published in Artificial Intelligence and Law, May 2024
Altmetric Badge

About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (62nd percentile)

Mentioned by

twitter
4 X users
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Exploring explainable AI in the tax domain
Published in
Artificial Intelligence and Law, May 2024
DOI 10.1007/s10506-024-09395-w
Authors

Łukasz Górski, Błażej Kuźniacki, Marco Almada, Kamil Tyliński, Madalena Calvo, Pablo Matias Asnaghi, Luciano Almada, Hilario Iñiguez, Fernando Rubianes, Octavio Pera, Juan Ignacio Nigrelli

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 08 May 2024.
All research outputs
#15,102,221
of 25,867,969 outputs
Outputs from Artificial Intelligence and Law
#106
of 237 outputs
Outputs of similar age
#53,897
of 149,786 outputs
Outputs of similar age from Artificial Intelligence and Law
#3
of 3 outputs
Altmetric has tracked 25,867,969 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 237 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.8. This one has gotten more attention than average, scoring higher than 53% 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 149,786 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 62% of its contemporaries.
We're also able to compare this research output to 3 others from the same source and published within six weeks on either side of this one.