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The dynamic stochastic topic block model for dynamic networks with textual edges

Overview of attention for article published in Statistics and Computing, September 2018
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (79th percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

Mentioned by

twitter
11 X users

Citations

dimensions_citation
9 Dimensions

Readers on

mendeley
13 Mendeley
Title
The dynamic stochastic topic block model for dynamic networks with textual edges
Published in
Statistics and Computing, September 2018
DOI 10.1007/s11222-018-9832-4
Authors

Marco Corneli, Charles Bouveyron, Pierre Latouche, Fabrice Rossi

X Demographics

X Demographics

The data shown below were collected from the profiles of 11 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 13 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 13 100%

Demographic breakdown

Readers by professional status Count As %
Lecturer 3 23%
Student > Ph. D. Student 2 15%
Researcher 2 15%
Student > Master 1 8%
Student > Doctoral Student 1 8%
Other 2 15%
Unknown 2 15%
Readers by discipline Count As %
Mathematics 3 23%
Computer Science 3 23%
Business, Management and Accounting 1 8%
Veterinary Science and Veterinary Medicine 1 8%
Psychology 1 8%
Other 1 8%
Unknown 3 23%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 9. 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 05 December 2018.
All research outputs
#3,584,879
of 23,103,903 outputs
Outputs from Statistics and Computing
#55
of 513 outputs
Outputs of similar age
#70,677
of 337,900 outputs
Outputs of similar age from Statistics and Computing
#1
of 6 outputs
Altmetric has tracked 23,103,903 research outputs across all sources so far. Compared to these this one has done well and is in the 84th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 513 research outputs from this source. They receive a mean Attention Score of 3.9. This one has done well, scoring higher than 89% 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 337,900 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 79% of its contemporaries.
We're also able to compare this research output to 6 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them