Content Bias Analysis
Content Bias Analysis is a systematic scholarly method used in fairness review to identify, quantify, and evaluate representational, procedural, or structural biases in the content generated or processed by computational models, distinguishing it from broader fairness assessments by focusing specifically on the informational and semantic properties of the content.
250
Publications
11K
Citations
636
Authors
362
Institutions
Publications per year
2017–2026
79
Parents
250
Shahab Saquib Sohail, Faiza Farhat, Yassine Himeur et al. · Journal of King Saud University - Computer and Information Sciences · 2023 · 180 citations · Full text
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362
Indiana University Bloomington
Bloomington, United States
4 h-index
8 publications
252 citations
Michigan State University
East Lansing, United States
4 h-index
5 publications
130 citations
Boston University
Boston, United States
4 h-index
5 publications
163 citations
The University of Texas at Austin
Austin, United States
4 h-index
8 publications
221 citations
Arizona State University
Tempe, United States
4 h-index
5 publications
125 citations

The University of Queensland
Brisbane, Australia
4 h-index
8 publications
328 citations

University of Toronto
Toronto, Canada
4 h-index
6 publications
222 citations
University of Michigan
Ann Arbor, United States
3 h-index
5 publications
86 citations
1–8 of 362
6 publications · 212 citations
6
h-index
5 publications · 177 citations
5
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SSJ · 3 publications · 250 citations
3
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CMM · 3 publications · 142 citations
3
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3 publications · 49 citations
3
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1–5