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Mapping the design-space of textual variability modeling languages: a refined analysis

Overview of attention for article published in International Journal on Software Tools for Technology Transfer, December 2014
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1 X user

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40 Mendeley
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Title
Mapping the design-space of textual variability modeling languages: a refined analysis
Published in
International Journal on Software Tools for Technology Transfer, December 2014
DOI 10.1007/s10009-014-0362-x
Authors

Holger Eichelberger, Klaus Schmid

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 40 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Czechia 1 3%
Unknown 39 98%

Demographic breakdown

Readers by professional status Count As %
Student > Master 7 18%
Student > Bachelor 7 18%
Student > Ph. D. Student 6 15%
Professor 3 8%
Researcher 3 8%
Other 4 10%
Unknown 10 25%
Readers by discipline Count As %
Computer Science 24 60%
Business, Management and Accounting 3 8%
Engineering 2 5%
Economics, Econometrics and Finance 1 3%
Unknown 10 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 30 January 2015.
All research outputs
#15,316,776
of 22,780,967 outputs
Outputs from International Journal on Software Tools for Technology Transfer
#77
of 111 outputs
Outputs of similar age
#213,917
of 361,222 outputs
Outputs of similar age from International Journal on Software Tools for Technology Transfer
#4
of 5 outputs
Altmetric has tracked 22,780,967 research outputs across all sources so far. This one is in the 22nd percentile – i.e., 22% of other outputs scored the same or lower than it.
So far Altmetric has tracked 111 research outputs from this source. They receive a mean Attention Score of 2.5. This one is in the 19th percentile – i.e., 19% 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 361,222 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 31st percentile – i.e., 31% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one.