Algorithmic Data Bias

Algorithmic Data Bias is a systematic error or distortion in data processing and decision-making that arises from the design, implementation, or training data of algorithms, leading to unfair or skewed outcomes in data-driven systems.

154

Publications

13.3K

Citations

656

Authors

333

Institutions

Publications per year

2017–2026

146

Authors

656

  1. CC
    Carlos Castillo

    Yahoo (Spain), Spain

    3 publications · 436 citations

    3

    h-index

  2. CR
    Christopher Rytting

    Brigham Young University, United States

    3 publications · 769 citations

    3

    h-index

  3. SX
    Shuyuan Xu

    Rutgers, The State University of New Jersey, United States

    3 publications · 127 citations

    3

    h-index

  4. NF
    Nancy Fulda

    Brigham Young University, United States

    3 publications · 769 citations

    3

    h-index

  5. YZ
    Yongfeng Zhang

    Rutgers, The State University of New Jersey, United States

    3 publications · 127 citations

    3

    h-index

1–5 of 656

Venues

  1. arXiv (Cornell University)

    Repository · 10 publications · 334 citations

    10

    h-index

  2. SSRN Electronic Journal

    Repository · 3 publications · 152 citations

    3

    h-index

  3. Internet Policy Review

    3 publications · 171 citations

    3

    h-index

  4. Journal of Medical Internet Research

    2 publications · 904 citations

    2

    h-index

  5. Computer Science & IT Research Journal

    2 publications · 83 citations

    2

    h-index

1–5