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Static slicing of Use Case Maps requirements models

Overview of attention for article published in Software & Systems Modeling, June 2018
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
2 tweeters

Citations

dimensions_citation
1 Dimensions

Readers on

mendeley
5 Mendeley
Title
Static slicing of Use Case Maps requirements models
Published in
Software & Systems Modeling, June 2018
DOI 10.1007/s10270-018-0680-7
Authors

Taha Binalialhag, Jameleddine Hassine, Daniel Amyot

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 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 %
Student > Master 3 60%
Professor > Associate Professor 1 20%
Unspecified 1 20%
Readers by discipline Count As %
Computer Science 3 60%
Unspecified 2 40%

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 07 July 2018.
All research outputs
#7,598,979
of 13,189,004 outputs
Outputs from Software & Systems Modeling
#133
of 404 outputs
Outputs of similar age
#139,095
of 269,847 outputs
Outputs of similar age from Software & Systems Modeling
#6
of 12 outputs
Altmetric has tracked 13,189,004 research outputs across all sources so far. This one is in the 40th percentile – i.e., 40% of other outputs scored the same or lower than it.
So far Altmetric has tracked 404 research outputs from this source. They receive a mean Attention Score of 1.7. This one has gotten more attention than average, scoring higher than 63% 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 269,847 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 45th percentile – i.e., 45% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 12 others from the same source and published within six weeks on either side of this one. This one is in the 41st percentile – i.e., 41% of its contemporaries scored the same or lower than it.