Computational Persuasion

Computational Persuasion is a computational method designed to systematically influence human attitudes, beliefs, or behaviors through algorithmically generated or optimized persuasive strategies grounded in principles of rhetoric, psychology, and data-driven modeling.

37

Publications

3.3K

Citations

75

Authors

35

Institutions

Publications per year

2017–2026

26

Authors

75

  1. AH
    Anthony Hunter

    University College London, United Kingdom

    6 publications · 171 citations

    6

    h-index

  2. FS
    Francesco Salvi

    École Polytechnique Fédérale de Lausanne, Switzerland

    2 publications · 145 citations

    3

    h-index

  3. RG
    Riccardo Gallotti

    Fondazione Bruno Kessler, Italy

    2 publications · 145 citations

    3

    h-index

  4. MH
    Manoel Horta Ribeiro

    École Polytechnique Fédérale de Lausanne, Switzerland

    2 publications · 145 citations

    3

    h-index

  5. EH
    Emmanuel Hadoux

    University College London, United Kingdom

    3 publications · 47 citations

    3

    h-index

1–5 of 75

Venues

  1. arXiv (Cornell University)

    Repository · 5 publications · 87 citations

    5

    h-index

  2. Proceedings of the AAAI Conference on Artificial Intelligence

    Conference · 2 publications · 38 citations

    3

    h-index

  3. Argument & Computation

    2 publications · 66 citations

    2

    h-index

  4. 1

    h-index

  5. Research Square

    Repository · 1 publications · 130 citations

    1

    h-index

1–5