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

Authors

636

  1. HD
    Hans‐Dieter Daniel

    ETH Zurich, Switzerland

    3 publications · 115 citations

    3

    h-index

  2. JS
    Joseph Stubbersfield

    Durham University, United Kingdom

    3 publications · 102 citations

    3

    h-index

  3. LB
    Lutz Bornmann

    Max Planck Society, Germany

    3 publications · 115 citations

    3

    h-index

  4. JS
    Julian Schaap

    Erasmus University Rotterdam, Netherlands

    2 publications · 40 citations

    2

    h-index

  5. JS
    Jiao Sun

    Ningxia Academy of Agriculture and Forestry Sciences, China

    2 publications · 123 citations

    2

    h-index

1–5 of 636

Venues

  1. PLoS ONE

    6 publications · 212 citations

    6

    h-index

  2. Journal of Broadcasting & Electronic Media

    5 publications · 177 citations

    5

    h-index

  3. Sociology of Sport Journal

    SSJ · 3 publications · 250 citations

    3

    h-index

  4. Communication Methods and Measures

    CMM · 3 publications · 142 citations

    3

    h-index

  5. Health Communication

    3 publications · 49 citations

    3

    h-index

1–5