An ensemble learning based approach for detecting and tracking COVID19 rumors

Sultan Noman Qasem, Mohammed Al-Sarem, Faisal Saeed*

*Corresponding author for this work

    Research output: Contribution to journalArticlepeer-review

    18 Citations (SciVal)
    Original languageEnglish
    Pages (from-to)1721-1747
    Number of pages27
    JournalComputers, Materials and Continua
    Volume70
    Issue number1
    DOIs
    Publication statusPublished (VoR) - 2021

    Funding

    The authors would like to thank Deanship of Scientific Research at Al Imam Mohammad ibn Saud Islamic university, Saudi Arabia, for financing this project under the grant no. (20-12-18-013). Funding Statement: This research was funded by the Deanship of Scientific Research, Mohammad Ibn Saud Islamic University, Saudi Arabia, Grant No. (20-12-18-013).

    FundersFunder number
    Deanship of Scientific Research at Al Imam Mohammad ibn Saud Islamic university
    Imam Mohammed Ibn Saud Islamic University20-12-18-013
    Deanship of Scientific Research, King Saud University

      Keywords

      • COVID-19
      • Rumor detection
      • Rumor tracking
      • Similarity techniques
      • Social media analytics

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