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DHPV: a distributed algorithm for large-scale graph partitioning

Overview of attention for article published in Journal of Big Data, September 2020
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About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (54th percentile)

Mentioned by

twitter
3 X users

Citations

dimensions_citation
10 Dimensions

Readers on

mendeley
22 Mendeley
Title
DHPV: a distributed algorithm for large-scale graph partitioning
Published in
Journal of Big Data, September 2020
DOI 10.1186/s40537-020-00357-y
Pubmed ID
Authors

Wilfried Yves Hamilton Adoni, Tarik Nahhal, Moez Krichen, Abdeltif El byed, Ismail Assayad

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 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 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 22 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 3 14%
Student > Master 2 9%
Student > Doctoral Student 2 9%
Unspecified 1 5%
Librarian 1 5%
Other 2 9%
Unknown 11 50%
Readers by discipline Count As %
Computer Science 3 14%
Medicine and Dentistry 2 9%
Agricultural and Biological Sciences 1 5%
Unspecified 1 5%
Physics and Astronomy 1 5%
Other 3 14%
Unknown 11 50%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 3. 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 19 October 2020.
All research outputs
#13,633,023
of 23,253,955 outputs
Outputs from Journal of Big Data
#160
of 350 outputs
Outputs of similar age
#186,203
of 376,573 outputs
Outputs of similar age from Journal of Big Data
#10
of 22 outputs
Altmetric has tracked 23,253,955 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 350 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.2. This one has gotten more attention than average, scoring higher than 54% 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 376,573 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 50% of its contemporaries.
We're also able to compare this research output to 22 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 54% of its contemporaries.