Computational Text Analysis

Computational Text Analysis is a methodological approach within digital humanities and political communication research that employs algorithmic, quantitative, and automated techniques to process, interpret, and derive meaningful patterns from large-scale textual data, distinguishing it from traditional qualitative content analysis through its reliance on computational scalability and formalized linguistic representation.

976

Publications

70.5K

Citations

2.7K

Authors

1.1K

Institutions

Publications per year

2017–2026

620

Authors

2.7K

  1. KB
    Kenneth Benoit

    Trinity College Dublin, Ireland

    6 publications · 1.1K citations

    6

    h-index

  2. AK
    Amir Karami

    University of South Carolina, United States

    6 publications · 144 citations

    6

    h-index

  3. NC
    Nello Cristianini

    University of Bristol, United Kingdom

    5 publications · 235 citations

    5

    h-index

  4. KM
    Kathleen M. Carley

    Carnegie Mellon University, United States

    5 publications · 201 citations

    5

    h-index

  5. MD
    Morteza Dehghani

    University of Southern California, United States

    5 publications · 325 citations

    5

    h-index

1–5 of 2.7K

Venues

  1. arXiv (Cornell University)

    Repository · 27 publications · 957 citations

    15

    h-index

  2. PLoS ONE

    12 publications · 618 citations

    12

    h-index

  3. Big Data & Society

    11 publications · 893 citations

    11

    h-index

  4. Communication Methods and Measures

    CMM · 10 publications · 1.2K citations

    10

    h-index

  5. Procedia Computer Science

    9 publications · 911 citations

    9

    h-index

1–5