Historical Text Mining

Historical Text Mining is a computational method within cultural analytics that systematically extracts, analyzes, and interprets textual patterns from historical documents to uncover contextual, semantic, or epistemic shifts over time.

77

Publications

3.2K

Citations

217

Authors

95

Institutions

Publications per year

2017–2026

27

Authors

217

  1. BA
    Beatrice Alex

    University of Edinburgh, United Kingdom

    5 publications · 151 citations

    5

    h-index

  2. EP
    Eva Pettersson

    Uppsala University, Sweden

    5 publications · 160 citations

    5

    h-index

  3. BM
    Beáta Megyesi

    Uppsala University, Sweden

    4 publications · 134 citations

    4

    h-index

  4. AJ
    Adam Jatowt

    Kyoto University, Japan

    4 publications · 148 citations

    4

    h-index

  5. CG
    Claire Grover

    University of Edinburgh, United Kingdom

    3 publications · 95 citations

    3

    h-index

1–5 of 217

Venues

  1. Digital Scholarship in the Humanities

    DSH · 4 publications · 252 citations

    4

    h-index

  2. 2

    h-index

  3. Pattern Recognition

    2 publications · 56 citations

    2

    h-index

  4. PLoS ONE

    2 publications · 132 citations

    2

    h-index

  5. DROPS (Schloss Dagstuhl – Leibniz Center for Informatics)

    Repository · 1 publications · 32 citations

    1

    h-index

1–5