↓ Skip to main content

Understanding Delegation Through Machine Learning: A Method and Application to the European Union

Overview of attention for article published in American Political Science Review, November 2019
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (88th percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

blogs
1 blog
twitter
15 X users

Citations

dimensions_citation
22 Dimensions

Readers on

mendeley
52 Mendeley
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
Understanding Delegation Through Machine Learning: A Method and Application to the European Union
Published in
American Political Science Review, November 2019
DOI 10.1017/s0003055419000522
Authors

L. JASON ANASTASOPOULOS, ANTHONY M. BERTELLI

X Demographics

X Demographics

The data shown below were collected from the profiles of 15 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 52 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 52 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 15 29%
Student > Master 8 15%
Student > Doctoral Student 7 13%
Professor 5 10%
Professor > Associate Professor 3 6%
Other 5 10%
Unknown 9 17%
Readers by discipline Count As %
Social Sciences 39 75%
Economics, Econometrics and Finance 2 4%
Business, Management and Accounting 1 2%
Computer Science 1 2%
Unknown 9 17%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 17. 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 29 June 2022.
All research outputs
#2,147,768
of 25,587,485 outputs
Outputs from American Political Science Review
#882
of 3,016 outputs
Outputs of similar age
#44,635
of 375,818 outputs
Outputs of similar age from American Political Science Review
#12
of 17 outputs
Altmetric has tracked 25,587,485 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 91st percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 3,016 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 26.9. This one has gotten more attention than average, scoring higher than 70% 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 375,818 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 88% of its contemporaries.
We're also able to compare this research output to 17 others from the same source and published within six weeks on either side of this one. This one is in the 35th percentile – i.e., 35% of its contemporaries scored the same or lower than it.