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Leveraging change point detection to discover natural experiments in data

Overview of attention for article published in EPJ Data Science, September 2022
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (61st percentile)

Mentioned by

twitter
7 X users

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
7 Mendeley
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Title
Leveraging change point detection to discover natural experiments in data
Published in
EPJ Data Science, September 2022
DOI 10.1140/epjds/s13688-022-00361-7
Pubmed ID
Authors

Yuzi He, Keith A. Burghardt, Kristina Lerman

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 7 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 7 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 43%
Professor > Associate Professor 1 14%
Other 1 14%
Student > Doctoral Student 1 14%
Unknown 1 14%
Readers by discipline Count As %
Social Sciences 3 43%
Economics, Econometrics and Finance 1 14%
Neuroscience 1 14%
Unknown 2 29%
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 07 September 2022.
All research outputs
#8,758,577
of 25,923,151 outputs
Outputs from EPJ Data Science
#385
of 461 outputs
Outputs of similar age
#156,177
of 434,259 outputs
Outputs of similar age from EPJ Data Science
#8
of 10 outputs
Altmetric has tracked 25,923,151 research outputs across all sources so far. This one is in the 43rd percentile – i.e., 43% of other outputs scored the same or lower than it.
So far Altmetric has tracked 461 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 37.2. This one is in the 16th percentile – i.e., 16% 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 434,259 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 61% of its contemporaries.
We're also able to compare this research output to 10 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.