Detection of Online Fake News Using N-Gram Analysis and Machine Learning Techniques

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Diffusion Models Beat GANs on Image Synthesis (2021, background): “images are a more direct concern, and detecting and mitigating propaganda and fake news based on generative models is an ongoing area of research [4, 3, 5].”
Fake News Detection Using Machine Learning Ensemble Methods (2020, methodology): “The study by Ahmed et al. [17] included extracting linguistic features such as n-grams from textual articles and training multiple ML models including K-nearest neighbor (KNN), support vector machine (SVM), logistic regression (LR), linear support vector machine (LSVM), decision tree (DT), and…”
FakeBERT: Fake news detection in social media with a BERT-based deep learning approach (2021, methodology): “In one of the studies, Ahmed et al [1] have utilised TF-IDF (Term Frequency-Inverse Document Frequency) as a feature extraction method with different machine learning models.”