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Identifying network structure similarity using spectral graph theory

Overview of attention for article published in Applied Network Science, January 2018
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (70th percentile)

Mentioned by

twitter
5 tweeters
peer_reviews
1 peer review site
facebook
1 Facebook page

Citations

dimensions_citation
36 Dimensions

Readers on

mendeley
49 Mendeley
Summary Twitter Peer reviews Facebook Dimensions citations
Title
Identifying network structure similarity using spectral graph theory
Published in
Applied Network Science, January 2018
DOI 10.1007/s41109-017-0042-3
Pubmed ID
30839726
Authors

Ralucca Gera, L. Alonso, Brian Crawford, Jeffrey House, J. A. Mendez-Bermudez, Thomas Knuth, Ryan Miller

View on publisher site

Twitter Demographics

The data shown below were collected from the profiles of 5 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 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 49 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 24%
Student > Master 6 12%
Researcher 5 10%
Student > Doctoral Student 4 8%
Student > Bachelor 3 6%
Other 5 10%
Unknown 14 29%
Readers by discipline Count As %
Computer Science 9 18%
Engineering 7 14%
Physics and Astronomy 3 6%
Agricultural and Biological Sciences 3 6%
Mathematics 2 4%
Other 8 16%
Unknown 17 35%

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 April 2018.
All research outputs
#6,565,101
of 23,801,276 outputs
Outputs from Applied Network Science
#176
of 519 outputs
Outputs of similar age
#131,294
of 443,827 outputs
Outputs of similar age from Applied Network Science
#1
of 2 outputs
Altmetric has tracked 23,801,276 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 519 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.4. This one has gotten more attention than average, scoring higher than 66% 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 443,827 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 70% of its contemporaries.
We're also able to compare this research output to 2 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

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