Computational Discourse Analysis

Computational Discourse Analysis is a systematic methodological framework within computational communication research that employs algorithmic and data-driven techniques to identify, classify, and interpret patterns of linguistic and symbolic meaning-making in large-scale textual interactions, distinguishing itself through its integration of natural language processing and social theory to uncover structured discursive practices.

113

Publications

11.4K

Citations

361

Authors

147

Institutions

Publications per year

2017–2026

33

Authors

361

  1. JD
    Johanna D. Moore

    University of Edinburgh, United Kingdom

    4 publications · 137 citations

    4

    h-index

  2. GA
    George Aaron Broadwell

    University at Albany, State University of New York, United States

    3 publications · 82 citations

    3

    h-index

  3. BW
    Bonnie Webber

    University of Edinburgh, United Kingdom

    3 publications · 188 citations

    3

    h-index

  4. AA
    Ahmed Abdelalí

    New Mexico State University, United States

    2 publications · 144 citations

    2

    h-index

  5. YM
    Yūji Matsumoto

    Nara Institute of Science and Technology, Japan

    2 publications · 874 citations

    2

    h-index

1–5 of 361

Venues

  1. The Association for Computational Linguistics

    6 publications · 3.9K citations

    6

    h-index

  2. arXiv (Cornell University)

    Repository · 2 publications · 171 citations

    2

    h-index

  3. Technical Communication Quarterly

    TCQ · 2 publications · 71 citations

    2

    h-index

  4. Meeting of the Association for Computational Linguistics

    Conference · 2 publications · 271 citations

    2

    h-index

  5. PLoS ONE

    2 publications · 119 citations

    2

    h-index

1–5