User Credibility Modeling

User Credibility Modeling is a computational framework that quantifies the reliability and trustworthiness of user-generated inputs in recommendation systems by analyzing behavioral patterns, social interactions, and content authenticity to distinguish credible users from unreliable ones.

106

Publications

5.5K

Citations

311

Authors

154

Institutions

Publications per year

2017–2026

44

Authors

311

  1. AW
    Adam Wierzbicki

    Polish-Japanese Academy of Information Technology, Poland

    4 publications · 161 citations

    4

    h-index

  2. RC
    Robin Cohen

    University of Waterloo, Canada

    4 publications · 82 citations

    4

    h-index

  3. KA
    Karl Aberer

    École Polytechnique Fédérale de Lausanne, Switzerland

    4 publications · 67 citations

    4

    h-index

  4. GP
    Gabriella Pasi

    University of Milano-Bicocca, Italy

    3 publications · 269 citations

    3

    h-index

  5. BA
    Bilal Abu-Salih

    University of Jordan, Jordan

    3 publications · 159 citations

    3

    h-index

1–5 of 311

Venues

  1. arXiv (Cornell University)

    Repository · 3 publications · 72 citations

    3

    h-index

  2. UTS ePRESS (University of Technology Sydney)

    Repository · 2 publications · 33 citations

    2

    h-index

  3. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 2 publications · 349 citations

    2

    h-index

  4. Information Processing & Management

    2 publications · 125 citations

    2

    h-index

  5. IEEE Internet of Things Journal

    2 publications · 106 citations

    2

    h-index

1–5