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Predicting individuals’ vulnerability to social engineering in social networks

Overview of attention for article published in Cybersecurity, March 2020
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (66th percentile)

Mentioned by

twitter
8 X users

Citations

dimensions_citation
25 Dimensions

Readers on

mendeley
200 Mendeley
Title
Predicting individuals’ vulnerability to social engineering in social networks
Published in
Cybersecurity, March 2020
DOI 10.1186/s42400-020-00047-5
Authors

Samar Muslah Albladi, George R. S. Weir

X Demographics

X Demographics

The data shown below were collected from the profiles of 8 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 200 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 200 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 19 10%
Student > Bachelor 19 10%
Student > Ph. D. Student 15 8%
Lecturer 12 6%
Student > Doctoral Student 9 5%
Other 27 14%
Unknown 99 50%
Readers by discipline Count As %
Computer Science 56 28%
Business, Management and Accounting 9 5%
Social Sciences 9 5%
Psychology 6 3%
Engineering 4 2%
Other 16 8%
Unknown 100 50%
Attention Score in Context

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 13 January 2022.
All research outputs
#7,006,706
of 25,400,630 outputs
Outputs from Cybersecurity
#12
of 48 outputs
Outputs of similar age
#128,544
of 386,398 outputs
Outputs of similar age from Cybersecurity
#3
of 3 outputs
Altmetric has tracked 25,400,630 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 48 research outputs from this source. They receive a mean Attention Score of 4.2. This one scored the same or higher as 36 of them.
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 386,398 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 66% 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.