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Events detection and community partition based on probabilistic snapshot for evolutionary social network

Overview of attention for article published in Peer-to-Peer Networking and Applications, February 2016
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1 X user

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9 Mendeley
Title
Events detection and community partition based on probabilistic snapshot for evolutionary social network
Published in
Peer-to-Peer Networking and Applications, February 2016
DOI 10.1007/s12083-016-0427-6
Authors

Zhongnan Zhang, Lei Hu, Ming Qiu, Fangyuan Gao

X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user 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 9 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 9 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 33%
Student > Doctoral Student 2 22%
Student > Bachelor 1 11%
Student > Postgraduate 1 11%
Unknown 2 22%
Readers by discipline Count As %
Computer Science 7 78%
Unknown 2 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 06 February 2016.
All research outputs
#18,438,457
of 22,844,985 outputs
Outputs from Peer-to-Peer Networking and Applications
#53
of 68 outputs
Outputs of similar age
#287,662
of 397,369 outputs
Outputs of similar age from Peer-to-Peer Networking and Applications
#1
of 2 outputs
Altmetric has tracked 22,844,985 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 68 research outputs from this source. They receive a mean Attention Score of 2.9. 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 397,369 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
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