Rumor Classification

Rumor Classification is a systematic method in computational social science that distinguishes false, unverified, or misleading information from factual content by analyzing linguistic, temporal, and propagation features within user-generated discourse on digital platforms.

125

Publications

9.2K

Citations

305

Authors

149

Institutions

Publications per year

2017–2026

107

Authors

305

  1. KB
    Kalina Bontcheva

    University of Sheffield, United Kingdom

    11 publications · 850 citations

    11

    h-index

  2. ML
    Maria Liakata

    University of Warwick, United Kingdom

    9 publications · 935 citations

    9

    h-index

  3. AZ
    Arkaitz Zubiaga

    Queen Mary University of London, United Kingdom

    9 publications · 961 citations

    9

    h-index

  4. LD
    Leon Derczynski

    University of Sheffield, United Kingdom

    5 publications · 431 citations

    5

    h-index

  5. RP
    Rob Procter

    University of Warwick, United Kingdom

    5 publications · 601 citations

    5

    h-index

1–5 of 305

Venues

  1. Information Processing & Management

    5 publications · 305 citations

    6

    h-index

  2. arXiv (Cornell University)

    Repository · 6 publications · 343 citations

    6

    h-index

  3. Multimedia Tools and Applications

    5 publications · 164 citations

    5

    h-index

  4. Expert Systems with Applications

    2 publications · 93 citations

    4

    h-index

  5. IEEE Access

    4 publications · 73 citations

    4

    h-index

1–5