文件列表:

Fake News Idea.docx (86308, 2022-03-13)
codes (0, 2022-03-13)
codes\CNN_BERT.ipynb (70820, 2022-03-13)
codes\Method1.ipynb (206687, 2022-03-13)
codes\Method2.ipynb (203047, 2022-03-13)
codes\Method3 Augmentation.ipynb (52430, 2022-03-13)
codes\Method3 Augmentation_2.ipynb (49211, 2022-03-13)
codes\XGB_tree_structure.pdf (298885, 2022-03-13)
codes\dataset.pdf (29273, 2022-03-13)
codes\fake-news-analytics-fn.ipynb (3938883, 2022-03-13)
codes\fake-news-analytics.ipynb (3897574, 2022-03-13)
codes\fakenews-70-20-10.ipynb (4008371, 2022-03-13)
codes\liar-70-20-10.ipynb (213156, 2022-03-13)
codes\method-1-liar-dataset.ipynb (203289, 2022-03-13)
papers (0, 2022-03-13)
papers\A novel self-learning semi-supervised deep learning network to detect fake news on social media_2021.pdf (408818, 2022-03-13)
papers\An ensemble machine learning approach through effective feature extraction to classify fake news.pdf (4512427, 2022-03-13)
papers\Analyzing and distinguishing fake and real news to mitigate the problem of disinformation.pdf (1834523, 2022-03-13)
papers\BerConvoNet_A_deeplearning_framework_for_fakenews_classification.pdf (1604364, 2022-03-13)
papers\Fake Detect- A Deep Learning Ensemble Model for Fake News Detection.pdf (3883762, 2022-03-13)
papers\Fake News Stance Detection Using DL architecture (CNN-LSTM).pdf (1525219, 2022-03-13)
papers\Fake news detection using deep learning models A novel approach.pdf (6542412, 2022-03-13)
papers\Feature Projection for Improved Text Classification.pdf (488493, 2022-03-13)
papers\MULTICHANNEL CNN WITH ATTENTION FOR TEXT CLASSIFICATION.pdf (860363, 2022-03-13)
papers\Transfer Learning from Transformers to FNC-1 Task.pdf (339266, 2022-03-13)

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