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A feature-based survey of model view approaches

Overview of attention for article published in Software and Systems Modeling, September 2017
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Good Attention Score compared to outputs of the same age and source (68th percentile)

Mentioned by

twitter
3 X users

Readers on

mendeley
60 Mendeley
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Title
A feature-based survey of model view approaches
Published in
Software and Systems Modeling, September 2017
DOI 10.1007/s10270-017-0622-9
Authors

Hugo Bruneliere, Erik Burger, Jordi Cabot, Manuel Wimmer

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 60 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 22%
Student > Master 9 15%
Researcher 5 8%
Student > Doctoral Student 4 7%
Lecturer 4 7%
Other 8 13%
Unknown 17 28%
Readers by discipline Count As %
Computer Science 32 53%
Engineering 7 12%
Business, Management and Accounting 2 3%
Agricultural and Biological Sciences 1 2%
Unknown 18 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 10 October 2017.
All research outputs
#13,981,574
of 23,849,058 outputs
Outputs from Software and Systems Modeling
#228
of 721 outputs
Outputs of similar age
#160,910
of 317,924 outputs
Outputs of similar age from Software and Systems Modeling
#4
of 16 outputs
Altmetric has tracked 23,849,058 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 721 research outputs from this source. They receive a mean Attention Score of 2.2. This one has gotten more attention than average, scoring higher than 60% 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 317,924 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 16 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 68% of its contemporaries.