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JANUS: A hypothesis-driven Bayesian approach for understanding edge formation in attributed multigraphs

Overview of attention for article published in Applied Network Science, June 2017
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (63rd percentile)

Mentioned by

twitter
6 tweeters

Citations

dimensions_citation
4 Dimensions

Readers on

mendeley
8 Mendeley
Title
JANUS: A hypothesis-driven Bayesian approach for understanding edge formation in attributed multigraphs
Published in
Applied Network Science, June 2017
DOI 10.1007/s41109-017-0036-1
Authors

Lisette Espín-Noboa, Florian Lemmerich, Markus Strohmaier, Philipp Singer

Twitter Demographics

The data shown below were collected from the profiles of 6 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 8 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 25%
Professor > Associate Professor 1 13%
Student > Postgraduate 1 13%
Student > Doctoral Student 1 13%
Unknown 3 38%
Readers by discipline Count As %
Computer Science 3 38%
Physics and Astronomy 1 13%
Unknown 4 50%

Attention Score in Context

This research output has an Altmetric Attention Score of 4. 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 03 July 2017.
All research outputs
#6,862,428
of 21,995,459 outputs
Outputs from Applied Network Science
#197
of 474 outputs
Outputs of similar age
#102,675
of 287,027 outputs
Outputs of similar age from Applied Network Science
#1
of 3 outputs
Altmetric has tracked 21,995,459 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 474 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 15.5. This one has gotten more attention than average, scoring higher than 58% 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 287,027 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 63% of its contemporaries.
We're also able to compare this research output to 3 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