@inproceedings{bade-etal-2024-social,
    title = "Social Media Fake News Classification Using Machine Learning Algorithm",
    author = "Bade, Girma  and
      Kolesnikova, Olga  and
      Sidorov, Grigori  and
      Oropeza, Jos{\'e}",
    editor = "Chakravarthi, Bharathi Raja  and
      Priyadharshini, Ruba  and
      Madasamy, Anand Kumar  and
      Thavareesan, Sajeetha  and
      Sherly, Elizabeth  and
      Nadarajan, Rajeswari  and
      Ravikiran, Manikandan",
    booktitle = "Proceedings of the Fourth Workshop on Speech, Vision, and Language Technologies for Dravidian Languages",
    month = mar,
    year = "2024",
    address = "St. Julian's, Malta",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2024.dravidianlangtech-1.4/",
    pages = "24--29",
    abstract = "The rise of social media has facilitated easier communication, information sharing, and current affairs updates. However, the prevalence of misleading and deceptive content, commonly referred to as fake news, poses a significant challenge. This paper focuses on the classification of fake news in Malayalam, a Dravidian language, utilizing natural language processing (NLP) techniques. To develop a model, we employed a random forest machine learning method on a dataset provided by a shared task(DravidianLangTech@EACL 2024)1. When evaluated by the separate test dataset, our developed model achieved a 0.71 macro F1 measure."
}