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    政大機構典藏 > 商學院 > 資訊管理學系 > 期刊論文 >  Item 140.119/154117
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    題名: A majority-based learning system for detecting misinformation
    作者: 杜雨儒
    Tu, Yu-Ju;Kao, Hanchun;Huang, Yu-Hsiang (John);Strader, Troy
    貢獻者: 資管系
    關鍵詞: Misinformation;fake news;detection;machine learning;majority-based
    日期: 2024-03
    上傳時間: 2024-10-28 11:42:54 (UTC+8)
    摘要: Combating misinformation is both a multifaceted problem and a pressing societal concern. In response, we propose a user-centric system founded on the majority vote model, offering flexibility and synergy in integrating established machine-learning methods or classifiers such as SVM, MLP, LSTM, RF, and XGB. Computational experiments demonstrate promising results in implementing our proposed system to identify text-based fake news, advertorials, and plagiarised information in social media. The dataset employed in these experiments is primarily sourced from volunteer contributors and fact-checking websites. The result evaluation indicators encompass balanced accuracy and F1 score. Overall, this study introduces a significant and autonomous countermeasure to address misinformation.
    關聯: Behaviour & Information Technology, pp.1-15
    資料類型: article
    DOI 連結: https://doi.org/10.1080/0144929X.2024.2326562
    DOI: 10.1080/0144929X.2024.2326562
    顯示於類別:[資訊管理學系] 期刊論文

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