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X Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Deep Reinforcement Learning for Cybersecurity Threat Detection and Protection: A Review
|
|---|---|
| Chapter number | 4 |
| Book title |
Secure Knowledge Management In The Artificial Intelligence Era
|
| Published in |
arXiv, June 2022
|
| DOI | 10.1007/978-3-030-97532-6_4 |
| Book ISBNs |
978-3-03-097531-9, 978-3-03-097532-6
|
| Authors |
Mohit Sewak, Sanjay K. Sahay, Hemant Rathore, Sewak, Mohit, Sahay, Sanjay K., Rathore, Hemant |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Switzerland | 1 | 25% |
| United States | 1 | 25% |
| Italy | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 49 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Master | 8 | 16% |
| Researcher | 5 | 10% |
| Student > Ph. D. Student | 3 | 6% |
| Lecturer | 2 | 4% |
| Student > Doctoral Student | 1 | 2% |
| Other | 3 | 6% |
| Unknown | 27 | 55% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 15 | 31% |
| Business, Management and Accounting | 2 | 4% |
| Engineering | 2 | 4% |
| Materials Science | 1 | 2% |
| Biochemistry, Genetics and Molecular Biology | 1 | 2% |
| Other | 0 | 0% |
| Unknown | 28 | 57% |
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 31 October 2023.
All research outputs
#7,030,001
of 24,911,633 outputs
Outputs from arXiv
#140,211
of 1,014,464 outputs
Outputs of similar age
#131,392
of 436,236 outputs
Outputs of similar age from arXiv
#4,632
of 35,453 outputs
Altmetric has tracked 24,911,633 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 1,014,464 research outputs from this source. They receive a mean Attention Score of 4.1. This one has done well, scoring higher than 85% 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 436,236 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 69% of its contemporaries.
We're also able to compare this research output to 35,453 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 86% of its contemporaries.