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Interpreting communities based on the evolution of a dynamic attributed network

Overview of attention for article published in Social Network Analysis and Mining, May 2015
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Mentioned by

twitter
2 X users

Citations

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12 Dimensions

Readers on

mendeley
23 Mendeley
Title
Interpreting communities based on the evolution of a dynamic attributed network
Published in
Social Network Analysis and Mining, May 2015
DOI 10.1007/s13278-015-0262-4
Authors

Günce Keziban Orman, Vincent Labatut, Marc Plantevit, Jean-François Boulicaut

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 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 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 23 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 4 17%
Student > Ph. D. Student 4 17%
Professor > Associate Professor 3 13%
Researcher 3 13%
Student > Doctoral Student 2 9%
Other 2 9%
Unknown 5 22%
Readers by discipline Count As %
Computer Science 13 57%
Social Sciences 2 9%
Business, Management and Accounting 1 4%
Earth and Planetary Sciences 1 4%
Pharmacology, Toxicology and Pharmaceutical Science 1 4%
Other 0 0%
Unknown 5 22%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 June 2015.
All research outputs
#19,294,479
of 23,891,012 outputs
Outputs from Social Network Analysis and Mining
#269
of 333 outputs
Outputs of similar age
#195,973
of 268,107 outputs
Outputs of similar age from Social Network Analysis and Mining
#12
of 12 outputs
Altmetric has tracked 23,891,012 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 333 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.4. This one is in the 8th percentile – i.e., 8% of its peers scored the same or lower than it.
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 268,107 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 14th percentile – i.e., 14% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 12 others from the same source and published within six weeks on either side of this one. This one is in the 8th percentile – i.e., 8% of its contemporaries scored the same or lower than it.