↓ Skip to main content

Botnet detection using graph-based feature clustering

Overview of attention for article published in Journal of Big Data, May 2017
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age

Mentioned by

twitter
1 tweeter

Citations

dimensions_citation
76 Dimensions

Readers on

mendeley
141 Mendeley
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 141 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Czechia 1 <1%
Unknown 140 99%

Demographic breakdown

Readers by professional status Count As %
Student > Master 30 21%
Student > Ph. D. Student 25 18%
Student > Bachelor 12 9%
Researcher 11 8%
Student > Doctoral Student 6 4%
Other 26 18%
Unknown 31 22%
Readers by discipline Count As %
Computer Science 69 49%
Engineering 17 12%
Business, Management and Accounting 3 2%
Agricultural and Biological Sciences 2 1%
Materials Science 2 1%
Other 8 6%
Unknown 40 28%

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
#11,704,772
of 18,009,382 outputs
Outputs from Journal of Big Data
#156
of 270 outputs
Outputs of similar age
#162,944
of 274,655 outputs
Outputs of similar age from Journal of Big Data
#1
of 1 outputs
Altmetric has tracked 18,009,382 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 270 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.3. This one is in the 28th percentile – i.e., 28% 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 274,655 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 31st percentile – i.e., 31% 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