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A tutorial on Bayesian inference for dynamical modeling of eye-movement control during reading

Overview of attention for article published in Journal of Mathematical Psychology, April 2024
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (71st percentile)

Mentioned by

twitter
7 X users

Readers on

mendeley
4 Mendeley
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Title
A tutorial on Bayesian inference for dynamical modeling of eye-movement control during reading
Published in
Journal of Mathematical Psychology, April 2024
DOI 10.1016/j.jmp.2024.102843
Authors

Ralf Engbert, Maximilian M. Rabe

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 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 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 4 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 1 25%
Professor > Associate Professor 1 25%
Researcher 1 25%
Unknown 1 25%
Readers by discipline Count As %
Psychology 2 50%
Unspecified 1 25%
Unknown 1 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 12 March 2024.
All research outputs
#7,480,204
of 26,396,170 outputs
Outputs from Journal of Mathematical Psychology
#115
of 472 outputs
Outputs of similar age
#99,942
of 349,900 outputs
Outputs of similar age from Journal of Mathematical Psychology
#2
of 4 outputs
Altmetric has tracked 26,396,170 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 472 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done well, scoring higher than 75% 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 349,900 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 71% of its contemporaries.
We're also able to compare this research output to 4 others from the same source and published within six weeks on either side of this one. This one has scored higher than 2 of them.