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Competition-Based Crowdsourcing Software Development: A Multi-Method Study from a Customer Perspective

Overview of attention for article published in IEEE Transactions on Software Engineering, March 2019
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (63rd percentile)

Mentioned by

twitter
2 tweeters

Citations

dimensions_citation
25 Dimensions

Readers on

mendeley
78 Mendeley
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Title
Competition-Based Crowdsourcing Software Development: A Multi-Method Study from a Customer Perspective
Published in
IEEE Transactions on Software Engineering, March 2019
DOI 10.1109/tse.2017.2774297
Authors

Klaas-Jan Stol, Bora Caglayan, Brian Fitzgerald

Twitter Demographics

The data shown below were collected from the profiles of 2 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 78 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 78 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 13 17%
Researcher 10 13%
Student > Bachelor 7 9%
Student > Ph. D. Student 6 8%
Student > Doctoral Student 4 5%
Other 14 18%
Unknown 24 31%
Readers by discipline Count As %
Computer Science 28 36%
Engineering 8 10%
Business, Management and Accounting 4 5%
Social Sciences 3 4%
Unspecified 1 1%
Other 5 6%
Unknown 29 37%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 14 March 2019.
All research outputs
#8,027,094
of 14,498,614 outputs
Outputs from IEEE Transactions on Software Engineering
#3,528
of 4,643 outputs
Outputs of similar age
#129,651
of 264,572 outputs
Outputs of similar age from IEEE Transactions on Software Engineering
#11
of 30 outputs
Altmetric has tracked 14,498,614 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 4,643 research outputs from this source. They receive a mean Attention Score of 4.0. This one is in the 23rd percentile – i.e., 23% 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 264,572 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 30 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.