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Evolution of communities of software: using tensor decompositions to compare software ecosystems

Overview of attention for article published in Applied Network Science, December 2019
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (63rd percentile)
  • Above-average Attention Score compared to outputs of the same age and source (59th percentile)

Mentioned by

twitter
8 tweeters

Readers on

mendeley
5 Mendeley
Title
Evolution of communities of software: using tensor decompositions to compare software ecosystems
Published in
Applied Network Science, December 2019
DOI 10.1007/s41109-019-0193-5
Authors

Oliver A. Blanthorn, Colin M. Caine, Eva M. Navarro-López

Twitter Demographics

The data shown below were collected from the profiles of 8 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 5 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 5 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 1 20%
Student > Ph. D. Student 1 20%
Other 1 20%
Student > Doctoral Student 1 20%
Unknown 1 20%
Readers by discipline Count As %
Computer Science 2 40%
Unspecified 1 20%
Social Sciences 1 20%
Medicine and Dentistry 1 20%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 05 March 2020.
All research outputs
#5,159,757
of 17,154,907 outputs
Outputs from Applied Network Science
#149
of 329 outputs
Outputs of similar age
#141,606
of 390,566 outputs
Outputs of similar age from Applied Network Science
#50
of 120 outputs
Altmetric has tracked 17,154,907 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 329 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 9.4. This one has gotten more attention than average, scoring higher than 54% 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 390,566 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 63% of its contemporaries.
We're also able to compare this research output to 120 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 59% of its contemporaries.