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Computer Security

Overview of attention for book
Attention for Chapter 1: Improving SIEM for Critical SCADA Water Infrastructures Using Machine Learning
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (72nd percentile)
  • High Attention Score compared to outputs of the same age and source (87th percentile)

Mentioned by

twitter
14 tweeters

Readers on

mendeley
15 Mendeley
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Chapter title
Improving SIEM for Critical SCADA Water Infrastructures Using Machine Learning
Chapter number 1
Book title
Computer Security
Published in
arXiv, September 2018
DOI 10.1007/978-3-030-12786-2_1
Book ISBNs
978-3-03-012785-5, 978-3-03-012786-2
Authors

Hanan Hindy, David Brosset, Ethan Bayne, Amar Seeam, Xavier Bellekens, Hindy, Hanan, Brosset, David, Bayne, Ethan, Seeam, Amar, Bellekens, Xavier

Twitter Demographics

The data shown below were collected from the profiles of 14 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 15 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 15 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 5 33%
Researcher 3 20%
Student > Master 2 13%
Professor > Associate Professor 1 7%
Unknown 4 27%
Readers by discipline Count As %
Computer Science 7 47%
Engineering 3 20%
Chemical Engineering 1 7%
Unknown 4 27%

Attention Score in Context

This research output has an Altmetric Attention Score of 6. 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 21 December 2019.
All research outputs
#3,669,303
of 15,899,742 outputs
Outputs from arXiv
#70,285
of 629,441 outputs
Outputs of similar age
#90,792
of 337,728 outputs
Outputs of similar age from arXiv
#3,157
of 24,872 outputs
Altmetric has tracked 15,899,742 research outputs across all sources so far. Compared to these this one has done well and is in the 76th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 629,441 research outputs from this source. They receive a mean Attention Score of 3.9. This one has done well, scoring higher than 88% 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 337,728 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 72% of its contemporaries.
We're also able to compare this research output to 24,872 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 87% of its contemporaries.