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Software Engineering for Self-Adaptive Systems II

Overview of attention for book
Overall attention for this book and its chapters
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (75th percentile)
  • Good Attention Score compared to outputs of the same age and source (72nd percentile)

Mentioned by

twitter
1 X user
facebook
1 Facebook page
wikipedia
2 Wikipedia pages

Readers on

mendeley
103 Mendeley
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Title
Software Engineering for Self-Adaptive Systems II
Published by
Lecture notes in computer science, January 2013
DOI 10.1007/978-3-642-35813-5
ISBNs
978-3-64-235812-8, 978-3-64-235813-5
Authors

Rogério de Lemos, Holger Giese, Hausi A. Müller, Mary Shaw, Lemos, Rogério, Giese, Holger, Müller, Hausi A, Shaw, Mary

Editors

Rogério de Lemos, Holger Giese, Hausi A. Müller, Mary Shaw

Timeline

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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.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 103 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 2 2%
Germany 2 2%
Colombia 1 <1%
Netherlands 1 <1%
South Africa 1 <1%
Unknown 96 93%

Demographic breakdown

Readers by professional status Count As %
Student > Master 20 19%
Student > Ph. D. Student 18 17%
Researcher 9 9%
Student > Bachelor 6 6%
Student > Doctoral Student 3 3%
Other 8 8%
Unknown 39 38%
Readers by discipline Count As %
Computer Science 54 52%
Engineering 7 7%
Business, Management and Accounting 1 <1%
Mathematics 1 <1%
Unknown 40 39%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 04 July 2016.
All research outputs
#6,801,268
of 24,226,848 outputs
Outputs from Lecture notes in computer science
#2,093
of 8,180 outputs
Outputs of similar age
#69,990
of 289,058 outputs
Outputs of similar age from Lecture notes in computer science
#85
of 318 outputs
Altmetric has tracked 24,226,848 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 8,180 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.1. This one has gotten more attention than average, scoring higher than 74% 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 289,058 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 75% of its contemporaries.
We're also able to compare this research output to 318 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 72% of its contemporaries.