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Block modelling in dynamic networks with non-homogeneous Poisson processes and exact ICL

Overview of attention for article published in Social Network Analysis and Mining, August 2016
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Good Attention Score compared to outputs of the same age and source (69th percentile)

Mentioned by

twitter
7 X users
facebook
3 Facebook pages

Citations

dimensions_citation
8 Dimensions

Readers on

mendeley
11 Mendeley
citeulike
2 CiteULike
Title
Block modelling in dynamic networks with non-homogeneous Poisson processes and exact ICL
Published in
Social Network Analysis and Mining, August 2016
DOI 10.1007/s13278-016-0368-3
Authors

Marco Corneli, Pierre Latouche, Fabrice Rossi

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 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 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 11 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 4 36%
Researcher 2 18%
Student > Master 2 18%
Unknown 3 27%
Readers by discipline Count As %
Mathematics 5 45%
Environmental Science 1 9%
Social Sciences 1 9%
Engineering 1 9%
Unknown 3 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 17 July 2017.
All research outputs
#7,658,506
of 23,314,015 outputs
Outputs from Social Network Analysis and Mining
#110
of 328 outputs
Outputs of similar age
#130,426
of 368,750 outputs
Outputs of similar age from Social Network Analysis and Mining
#3
of 13 outputs
Altmetric has tracked 23,314,015 research outputs across all sources so far. This one is in the 44th percentile – i.e., 44% of other outputs scored the same or lower than it.
So far Altmetric has tracked 328 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.5. This one has gotten more attention than average, scoring higher than 61% 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 368,750 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 13 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 69% of its contemporaries.