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The law of large numbers for large stable matchings

Overview of attention for article published in Journal of Econometrics, April 2024
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  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
3 X users

Readers on

mendeley
6 Mendeley
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Title
The law of large numbers for large stable matchings
Published in
Journal of Econometrics, April 2024
DOI 10.1016/j.jeconom.2024.105742
Authors

Jacob Schwartz, Kyungchul Song

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 6 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 6 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 3 50%
Professor > Associate Professor 1 17%
Professor 1 17%
Unknown 1 17%
Readers by discipline Count As %
Unspecified 3 50%
Economics, Econometrics and Finance 2 33%
Engineering 1 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 25 April 2024.
All research outputs
#17,032,842
of 25,806,763 outputs
Outputs from Journal of Econometrics
#2,169
of 2,933 outputs
Outputs of similar age
#118,650
of 247,847 outputs
Outputs of similar age from Journal of Econometrics
#40
of 64 outputs
Altmetric has tracked 25,806,763 research outputs across all sources so far. This one is in the 31st percentile – i.e., 31% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,933 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.1. This one is in the 23rd percentile – i.e., 23% 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 247,847 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 64 others from the same source and published within six weeks on either side of this one. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.