Recommendation Bias

Recommendation Bias is a systematic distortion in algorithmic content curation processes whereby user exposure to political information is skewed due to the preferential amplification of specific viewpoints, engagement-driven optimization, or platform design choices inherent in recommender systems.

132

Publications

8.1K

Citations

394

Authors

191

Institutions

Publications per year

2017–2026

110

Authors

394

  1. XH
    Xiangnan He

    University of Science and Technology of China, China

    8 publications · 1.4K citations

    8

    h-index

  2. JC
    Jiawei Chen

    Zhejiang University, China

    6 publications · 938 citations

    6

    h-index

  3. FF
    Fuli Feng

    University of Science and Technology of China, China

    5 publications · 1.2K citations

    5

    h-index

  4. HA
    Himan Abdollahpouri

    DePaul University, United States

    4 publications · 265 citations

    4

    h-index

  5. MB
    Marc Bourreau

    Télécom Paris, France

    3 publications · 90 citations

    3

    h-index

1–5 of 394

Venues

  1. arXiv (Cornell University)

    Repository · 13 publications · 511 citations

    12

    h-index

  2. Information Processing & Management

    6 publications · 389 citations

    6

    h-index

  3. SSRN Electronic Journal

    Repository · 5 publications · 204 citations

    5

    h-index

  4. ACM Transactions on Information Systems

    4 publications · 670 citations

    4

    h-index

  5. Europhysics Letters (EPL)

    3 publications · 138 citations

    3

    h-index

1–5