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Developing a mathematical model of the co-author recommender system using graph mining techniques and big data applications

Overview of attention for article published in Journal of Big Data, March 2021
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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 (56th percentile)

Mentioned by

twitter
3 X users

Readers on

mendeley
38 Mendeley
Title
Developing a mathematical model of the co-author recommender system using graph mining techniques and big data applications
Published in
Journal of Big Data, March 2021
DOI 10.1186/s40537-021-00432-y
Authors

Fezzeh Ebrahimi, Asefeh Asemi, Amin Nezarat, Andrea Ko

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

Geographical breakdown

Country Count As %
Unknown 38 100%

Demographic breakdown

Readers by professional status Count As %
Lecturer 6 16%
Student > Master 5 13%
Student > Bachelor 4 11%
Student > Ph. D. Student 3 8%
Researcher 2 5%
Other 5 13%
Unknown 13 34%
Readers by discipline Count As %
Computer Science 10 26%
Engineering 6 16%
Business, Management and Accounting 3 8%
Agricultural and Biological Sciences 2 5%
Biochemistry, Genetics and Molecular Biology 1 3%
Other 2 5%
Unknown 14 37%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 11 March 2021.
All research outputs
#13,737,729
of 23,287,285 outputs
Outputs from Journal of Big Data
#166
of 351 outputs
Outputs of similar age
#205,889
of 421,249 outputs
Outputs of similar age from Journal of Big Data
#7
of 16 outputs
Altmetric has tracked 23,287,285 research outputs across all sources so far. This one is in the 39th percentile – i.e., 39% of other outputs scored the same or lower than it.
So far Altmetric has tracked 351 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.3. This one is in the 49th percentile – i.e., 49% 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 421,249 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 49th percentile – i.e., 49% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 16 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 56% of its contemporaries.