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Machine learning and structural econometrics: contrasts and synergies

Overview of attention for article published in Econometrics Journal, August 2020
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#7 of 201)
  • High Attention Score compared to outputs of the same age (83rd percentile)
  • Good Attention Score compared to outputs of the same age and source (66th percentile)

Mentioned by

twitter
20 tweeters

Readers on

mendeley
16 Mendeley
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Title
Machine learning and structural econometrics: contrasts and synergies
Published in
Econometrics Journal, August 2020
DOI 10.1093/ectj/utaa019
Authors

Fedor Iskhakov, John Rust, Bertel Schjerning

Twitter Demographics

The data shown below were collected from the profiles of 20 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 16 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 16 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 25%
Professor > Associate Professor 3 19%
Researcher 2 13%
Student > Master 1 6%
Other 1 6%
Other 1 6%
Unknown 4 25%
Readers by discipline Count As %
Economics, Econometrics and Finance 8 50%
Psychology 1 6%
Social Sciences 1 6%
Engineering 1 6%
Unknown 5 31%

Attention Score in Context

This research output has an Altmetric Attention Score of 13. 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 December 2020.
All research outputs
#1,644,037
of 16,652,557 outputs
Outputs from Econometrics Journal
#7
of 201 outputs
Outputs of similar age
#48,750
of 304,752 outputs
Outputs of similar age from Econometrics Journal
#3
of 6 outputs
Altmetric has tracked 16,652,557 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 201 research outputs from this source. They receive a mean Attention Score of 3.7. This one has done particularly well, scoring higher than 97% 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 304,752 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 83% of its contemporaries.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than 3 of them.