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Stochastic block models with multiple continuous attributes

Overview of attention for article published in Applied Network Science, August 2019
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (83rd percentile)
  • Good Attention Score compared to outputs of the same age and source (74th percentile)

Mentioned by

twitter
23 X users

Citations

dimensions_citation
41 Dimensions

Readers on

mendeley
38 Mendeley
Title
Stochastic block models with multiple continuous attributes
Published in
Applied Network Science, August 2019
DOI 10.1007/s41109-019-0170-z
Authors

Natalie Stanley, Thomas Bonacci, Roland Kwitt, Marc Niethammer, Peter J. Mucha

X Demographics

X Demographics

The data shown below were collected from the profiles of 23 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 38 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 38 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 21%
Researcher 5 13%
Student > Master 3 8%
Student > Bachelor 2 5%
Professor > Associate Professor 2 5%
Other 5 13%
Unknown 13 34%
Readers by discipline Count As %
Mathematics 7 18%
Computer Science 4 11%
Social Sciences 2 5%
Physics and Astronomy 2 5%
Philosophy 1 3%
Other 7 18%
Unknown 15 39%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 12. 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 September 2019.
All research outputs
#2,910,173
of 24,458,924 outputs
Outputs from Applied Network Science
#74
of 542 outputs
Outputs of similar age
#58,450
of 351,310 outputs
Outputs of similar age from Applied Network Science
#9
of 31 outputs
Altmetric has tracked 24,458,924 research outputs across all sources so far. Compared to these this one has done well and is in the 88th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 542 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 13.7. This one has done well, scoring higher than 86% 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 351,310 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 83% of its contemporaries.
We're also able to compare this research output to 31 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 74% of its contemporaries.