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Usage and attribution of Stack Overflow code snippets in GitHub projects

Overview of attention for article published in Empirical Software Engineering, October 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#39 of 462)
  • High Attention Score compared to outputs of the same age (82nd percentile)
  • High Attention Score compared to outputs of the same age and source (82nd percentile)

Mentioned by

twitter
10 tweeters
facebook
1 Facebook page
q&a
1 Q&A thread

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
8 Mendeley
Title
Usage and attribution of Stack Overflow code snippets in GitHub projects
Published in
Empirical Software Engineering, October 2018
DOI 10.1007/s10664-018-9650-5
Authors

Sebastian Baltes, Stephan Diehl

Twitter Demographics

The data shown below were collected from the profiles of 10 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 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 38%
Student > Ph. D. Student 2 25%
Lecturer > Senior Lecturer 1 13%
Student > Doctoral Student 1 13%
Professor > Associate Professor 1 13%
Other 0 0%
Readers by discipline Count As %
Computer Science 6 75%
Unspecified 1 13%
Physics and Astronomy 1 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 11. 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 18 July 2019.
All research outputs
#1,442,433
of 13,384,384 outputs
Outputs from Empirical Software Engineering
#39
of 462 outputs
Outputs of similar age
#47,294
of 265,837 outputs
Outputs of similar age from Empirical Software Engineering
#3
of 17 outputs
Altmetric has tracked 13,384,384 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 462 research outputs from this source. They receive a mean Attention Score of 3.8. This one has done particularly well, scoring higher than 91% 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 265,837 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 82% 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 has done well, scoring higher than 82% of its contemporaries.