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Context-Based Patterns in Machine Learning Bias and Fairness Metrics: A Sensitive Attributes-Based Approach

Overview of attention for article published in Big Data and Cognitive Computing, January 2023
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55 Mendeley
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Article details
Title
Context-Based Patterns in Machine Learning Bias and Fairness Metrics: A Sensitive Attributes-Based Approach
Published in
Big Data and Cognitive Computing, January 2023
DOI 10.3390/bdcc7010027
Authors

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Timeline Attention over time Attention Score history
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X Demographics

X Demographics

The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley demographics

Mendeley demographics

The data shown below were compiled from readership statistics for 55 Mendeley readers of this research output. Click here to see the associated Mendeley record.
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Geographical breakdown

Geographical breakdown
Country Count As %
Unknown 55 100%

Demographic breakdown

Readers by professional status
Readers by professional status Count As %
Student > Master 4 7%
Researcher 4 7%
Professor 3 5%
Lecturer 2 4%
Student > Bachelor 2 4%
Other 3 5%
Unknown 37 67%
Readers by discipline
Readers by discipline Count As %
Computer Science 9 16%
Economics, Econometrics and Finance 2 4%
Engineering 2 4%
Arts and Humanities 1 2%
Mathematics 1 2%
Other 3 5%
Unknown 37 67%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 29 August 2023.
All research outputs
#19,809,361
of 24,343,193 outputs
Outputs from Big Data and Cognitive Computing
#244
of 393 outputs
Outputs of similar age
#322,090
of 442,193 outputs
Outputs of similar age from Big Data and Cognitive Computing
#18
of 33 outputs
Altmetric has tracked 24,343,193 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 393 research outputs from this source. They receive a mean Attention Score of 2.5. This one is in the 1st percentile – i.e., 1% 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 442,193 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 15th percentile – i.e., 15% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 33 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.