↓ Skip to main content

Modeling Performance of Microservices Systems with Growth Theory

Overview of attention for article published in Empirical Software Engineering, January 2022
Altmetric Badge

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 X users

Readers on

mendeley
70 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Article details
Title
Modeling Performance of Microservices Systems with Growth Theory
Published in
Empirical Software Engineering, January 2022
DOI 10.1007/s10664-021-10088-0
Pubmed ID
Authors

Login to access the Attention Digest and the Sentiment Analysis related to this output.

Timeline Attention over time Attention Score history
Login to access the full charts related to this output.
Activity
Login to access the full charts related to this output.
X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 70 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Login to view Mendeley reader trends over time.

Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 70 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Bachelor 6 9%
Student > Ph. D. Student 6 9%
Student > Master 2 3%
Researcher 2 3%
Professor > Associate Professor 2 3%
Other 5 7%
Unknown 47 67%
Readers by discipline
Readers by discipline Count As %
Computer Science 15 21%
Engineering 2 3%
Arts and Humanities 1 1%
Unspecified 1 1%
Environmental Science 1 1%
Other 3 4%
Unknown 47 67%
Attention Score in Context

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 11 January 2022.
All research outputs
#14,255,539
of 22,858,915 outputs
Outputs from Empirical Software Engineering
#451
of 705 outputs
Outputs of similar age
#240,905
of 503,119 outputs
Outputs of similar age from Empirical Software Engineering
#6
of 14 outputs
Altmetric has tracked 22,858,915 research outputs across all sources so far. This one is in the 35th percentile – i.e., 35% of other outputs scored the same or lower than it.
So far Altmetric has tracked 705 research outputs from this source. They receive a mean Attention Score of 4.8. This one is in the 32nd percentile – i.e., 32% 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 503,119 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 14 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 50% of its contemporaries.