False Rumor Detection

False Rumor Detection is a computational method designed to identify and verify the veracity of unverified information in digital communication by distinguishing false rumors from true or neutral claims through linguistic, temporal, and network-based analysis.

177

Publications

14.2K

Citations

521

Authors

249

Institutions

Publications per year

2017–2026

151

Authors

521

  1. ML
    Maria Liakata

    University of Warwick, United Kingdom

    11 publications · 1.7K citations

    11

    h-index

  2. AZ
    Arkaitz Zubiaga

    Queen Mary University of London, United Kingdom

    10 publications · 1.6K citations

    10

    h-index

  3. KB
    Kalina Bontcheva

    University of Sheffield, United Kingdom

    8 publications · 777 citations

    8

    h-index

  4. RP
    Rob Procter

    University of Warwick, United Kingdom

    8 publications · 1.4K citations

    8

    h-index

  5. PZ
    Peng Zheng

    National University of Defense Technology, China

    4 publications · 140 citations

    6

    h-index

1–5 of 521

Venues

  1. Information Processing & Management

    10 publications · 364 citations

    11

    h-index

  2. Expert Systems with Applications

    7 publications · 312 citations

    9

    h-index

  3. arXiv (Cornell University)

    Repository · 8 publications · 402 citations

    8

    h-index

  4. Neurocomputing

    5 publications · 156 citations

    7

    h-index

  5. Knowledge-Based Systems

    4 publications · 212 citations

    6

    h-index

1–5