The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
Timeline
Mendeley readers
Attention Score in Context
Title |
Workplace Assignment to Workers in Synthetic Populations in Japan
|
---|---|
Published in |
IEEE Transactions on Computational Social Systems, November 2022
|
DOI | 10.1109/tcss.2022.3217614 |
Authors |
Tadahiko Murata, Daiki Iwase, Takuya Harada |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 4 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Researcher | 1 | 25% |
Student > Postgraduate | 1 | 25% |
Student > Master | 1 | 25% |
Unknown | 1 | 25% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 1 | 25% |
Earth and Planetary Sciences | 1 | 25% |
Social Sciences | 1 | 25% |
Unknown | 1 | 25% |
Attention Score in Context
This research output has an Altmetric Attention Score of 72. 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 January 2023.
All research outputs
#589,513
of 25,392,582 outputs
Outputs from IEEE Transactions on Computational Social Systems
#3
of 159 outputs
Outputs of similar age
#14,164
of 440,986 outputs
Outputs of similar age from IEEE Transactions on Computational Social Systems
#1
of 7 outputs
Altmetric has tracked 25,392,582 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 97th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 159 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.9. This one has done particularly well, scoring higher than 98% 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 440,986 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 96% of its contemporaries.
We're also able to compare this research output to 7 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