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Detecting malicious accounts in permissionless blockchains using temporal graph properties

Overview of attention for article published in Applied Network Science, February 2021
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About this Attention Score

  • Good Attention Score compared to outputs of the same age (67th percentile)
  • Above-average Attention Score compared to outputs of the same age and source (62nd percentile)

Mentioned by

twitter
7 X users

Citations

dimensions_citation
21 Dimensions

Readers on

mendeley
51 Mendeley
Title
Detecting malicious accounts in permissionless blockchains using temporal graph properties
Published in
Applied Network Science, February 2021
DOI 10.1007/s41109-020-00338-3
Authors

Rachit Agarwal, Shikhar Barve, Sandeep Kumar Shukla

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 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 51 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 51 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 8 16%
Student > Ph. D. Student 5 10%
Professor 4 8%
Student > Doctoral Student 3 6%
Student > Bachelor 2 4%
Other 8 16%
Unknown 21 41%
Readers by discipline Count As %
Computer Science 18 35%
Engineering 7 14%
Business, Management and Accounting 2 4%
Social Sciences 2 4%
Agricultural and Biological Sciences 1 2%
Other 2 4%
Unknown 19 37%
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 06 May 2021.
All research outputs
#6,493,964
of 23,278,709 outputs
Outputs from Applied Network Science
#181
of 513 outputs
Outputs of similar age
#163,485
of 509,267 outputs
Outputs of similar age from Applied Network Science
#10
of 27 outputs
Altmetric has tracked 23,278,709 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 513 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 14.4. This one has gotten more attention than average, scoring higher than 64% 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 509,267 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 67% of its contemporaries.
We're also able to compare this research output to 27 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 62% of its contemporaries.