Hedging Detection

Hedging Detection is a computational linguistic task that identifies linguistic markers of uncertainty or caution in academic texts to determine the degree of commitment authors exhibit toward their claims.

9

Publications

324

Citations

28

Authors

28

Institutions

Publications per year

2017–2026

4

Authors

28

  1. HK
    Halil Kilicoglu

    United States National Library of Medicine, United States

    2 publications · 137 citations

    2

    h-index

  2. SB
    Sabine Bergler

    Concordia University, Canada

    2 publications · 137 citations

    2

    h-index

  3. TM
    Tamara M. Gaidukova

    Peoples' Friendship University of Russia, Russia

    1 publications · 18 citations

    1

    h-index

  4. PC
    Paula Chesley

    University of Minnesota, United States

    1 publications · 35 citations

    1

    h-index

  5. EA
    Elie A. Akl

    McMaster University, Canada

    1 publications · 35 citations

    1

    h-index

1–5 of 28

Venues

  1. BMC Bioinformatics

    1 publications · 126 citations

    1

    h-index

  2. DergiPark (Istanbul University)

    Repository · 1 publications · 58 citations

    1

    h-index

  3. Dialnet (Universidad de la Rioja)

    Repository · 1 publications · 16 citations

    1

    h-index

  4. Scientometrics

    1 publications · 27 citations

    1

    h-index

  5. Training Language and Culture

    TLC · 1 publications · 18 citations

    1

    h-index

1–5