Algorithmic Storytelling

Algorithmic Storytelling is a computational narrative methodology that systematically generates or structures narrative content through algorithmically driven decision processes, distinguishing it from manual or purely heuristic storytelling approaches by its reliance on formalized rules, data-driven models, or automated reasoning to produce coherent and contextually appropriate narratives.

52

Publications

2.4K

Citations

120

Authors

63

Institutions

Publications per year

2017–2026

30

Authors

120

  1. MR
    Mark Riedl

    Georgia Institute of Technology, United States

    3 publications · 94 citations

    3

    h-index

  2. MM
    Michael Mateas

    University of California, Santa Cruz, United States

    3 publications · 126 citations

    3

    h-index

  3. RF
    Rachelyn Farrell

    University of New Orleans, United States

    2 publications · 51 citations

    2

    h-index

  4. NW
    Noah Wardrip–Fruin

    University of California, Santa Cruz, United States

    2 publications · 65 citations

    2

    h-index

  5. RM
    R. Michael Young

    North Carolina State University, United States

    2 publications · 34 citations

    2

    h-index

1–5 of 120

Venues

  1. 8

    h-index

  2. Digital Journalism

    2 publications · 225 citations

    2

    h-index

  3. 2

    h-index

  4. New Media & Society

    2 publications · 49 citations

    2

    h-index

  5. Cultural Sociology

    1 publications · 18 citations

    1

    h-index

1–5