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Using dynamic models to support inferences of insider threat risk

Overview of attention for article published in Computational and Mathematical Organization Theory, January 2016
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (68th percentile)

Mentioned by

patent
1 patent
facebook
1 Facebook page

Citations

dimensions_citation
7 Dimensions

Readers on

mendeley
60 Mendeley
Title
Using dynamic models to support inferences of insider threat risk
Published in
Computational and Mathematical Organization Theory, January 2016
DOI 10.1007/s10588-016-9209-1
Authors

Paul J. Sticha, Elise T. Axelrad

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 60 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 15 25%
Student > Ph. D. Student 14 23%
Student > Doctoral Student 6 10%
Researcher 5 8%
Lecturer 3 5%
Other 8 13%
Unknown 9 15%
Readers by discipline Count As %
Computer Science 21 35%
Business, Management and Accounting 7 12%
Engineering 6 10%
Psychology 4 7%
Social Sciences 3 5%
Other 7 12%
Unknown 12 20%
Attention Score in Context

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 07 December 2021.
All research outputs
#7,660,617
of 23,854,458 outputs
Outputs from Computational and Mathematical Organization Theory
#28
of 96 outputs
Outputs of similar age
#121,710
of 400,045 outputs
Outputs of similar age from Computational and Mathematical Organization Theory
#2
of 3 outputs
Altmetric has tracked 23,854,458 research outputs across all sources so far. This one has received more attention than most of these and is in the 67th percentile.
So far Altmetric has tracked 96 research outputs from this source. They receive a mean Attention Score of 4.4. This one has gotten more attention than average, scoring higher than 69% 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 400,045 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 68% 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.