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Generating automatically labeled data for author name disambiguation: an iterative clustering method

Overview of attention for article published in Scientometrics, November 2018
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  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
4 X users

Citations

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25 Dimensions

Readers on

mendeley
49 Mendeley
Title
Generating automatically labeled data for author name disambiguation: an iterative clustering method
Published in
Scientometrics, November 2018
DOI 10.1007/s11192-018-2968-3
Authors

Jinseok Kim, Jinmo Kim, Jason Owen-Smith

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 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 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 49 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 14%
Other 6 12%
Student > Bachelor 6 12%
Student > Doctoral Student 4 8%
Student > Master 4 8%
Other 6 12%
Unknown 16 33%
Readers by discipline Count As %
Computer Science 16 33%
Social Sciences 10 20%
Economics, Econometrics and Finance 2 4%
Immunology and Microbiology 1 2%
Mathematics 1 2%
Other 1 2%
Unknown 18 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 08 February 2021.
All research outputs
#15,185,041
of 24,093,053 outputs
Outputs from Scientometrics
#1,944
of 2,800 outputs
Outputs of similar age
#244,066
of 445,315 outputs
Outputs of similar age from Scientometrics
#29
of 43 outputs
Altmetric has tracked 24,093,053 research outputs across all sources so far. This one is in the 34th percentile – i.e., 34% of other outputs scored the same or lower than it.
So far Altmetric has tracked 2,800 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 10.7. 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 445,315 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 42nd percentile – i.e., 42% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 43 others from the same source and published within six weeks on either side of this one. This one is in the 32nd percentile – i.e., 32% of its contemporaries scored the same or lower than it.