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Botnet detection using graph-based feature clustering

Overview of attention for article published in Journal of Big Data, May 2017
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About this Attention Score

  • Average Attention Score compared to outputs of the same age

Mentioned by

twitter
1 tweeter

Citations

dimensions_citation
17 Dimensions

Readers on

mendeley
57 Mendeley
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Title
Botnet detection using graph-based feature clustering
Published in
Journal of Big Data, May 2017
DOI 10.1186/s40537-017-0074-7
Authors

Sudipta Chowdhury, Mojtaba Khanzadeh, Ravi Akula, Fangyan Zhang, Song Zhang, Hugh Medal, Mohammad Marufuzzaman, Linkan Bian

Twitter Demographics

The data shown below were collected from the profile of 1 tweeter 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 57 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Czechia 1 2%
Unknown 56 98%

Demographic breakdown

Readers by professional status Count As %
Student > Master 14 25%
Unspecified 12 21%
Student > Ph. D. Student 11 19%
Professor > Associate Professor 5 9%
Researcher 5 9%
Other 10 18%
Readers by discipline Count As %
Computer Science 26 46%
Unspecified 17 30%
Engineering 11 19%
Business, Management and Accounting 1 2%
Agricultural and Biological Sciences 1 2%
Other 1 2%

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 12 May 2017.
All research outputs
#8,264,243
of 13,183,545 outputs
Outputs from Journal of Big Data
#104
of 147 outputs
Outputs of similar age
#150,285
of 263,981 outputs
Outputs of similar age from Journal of Big Data
#1
of 1 outputs
Altmetric has tracked 13,183,545 research outputs across all sources so far. This one is in the 23rd percentile – i.e., 23% of other outputs scored the same or lower than it.
So far Altmetric has tracked 147 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.7. This one is in the 7th percentile – i.e., 7% 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 263,981 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 33rd percentile – i.e., 33% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 1 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