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Understanding semi-structured merge conflict characteristics in open-source Java projects

Overview of attention for article published in Empirical Software Engineering, December 2017
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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 (#45 of 707)
  • High Attention Score compared to outputs of the same age (86th percentile)
  • High Attention Score compared to outputs of the same age and source (89th percentile)

Mentioned by

twitter
13 X users
patent
1 patent
facebook
1 Facebook page

Citations

dimensions_citation
37 Dimensions

Readers on

mendeley
36 Mendeley
Title
Understanding semi-structured merge conflict characteristics in open-source Java projects
Published in
Empirical Software Engineering, December 2017
DOI 10.1007/s10664-017-9586-1
Authors

Paola Accioly, Paulo Borba, Guilherme Cavalcanti

X Demographics

X Demographics

The data shown below were collected from the profiles of 13 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 36 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 36 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 17%
Student > Master 4 11%
Student > Doctoral Student 3 8%
Student > Bachelor 2 6%
Professor 2 6%
Other 5 14%
Unknown 14 39%
Readers by discipline Count As %
Computer Science 20 56%
Engineering 1 3%
Unknown 15 42%
Attention Score in Context

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 12 October 2021.
All research outputs
#2,415,851
of 23,012,811 outputs
Outputs from Empirical Software Engineering
#45
of 707 outputs
Outputs of similar age
#57,323
of 440,658 outputs
Outputs of similar age from Empirical Software Engineering
#3
of 28 outputs
Altmetric has tracked 23,012,811 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 707 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done particularly well, scoring higher than 93% 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 440,658 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 86% of its contemporaries.
We're also able to compare this research output to 28 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 89% of its contemporaries.