FaKy: A feature extraction library to detect the truthfulness of a text
The transparency and explainability of fake news detection is a crucial feature to enhance the trustability of the assessments and, consequently, their effectiveness. Textual features have shown their potential to help identify fake news in a transparent manner. In this paper, we survey a list of textual features, evaluate their usefulness in predicting fake news by testing them on a real-world dataset, and collect them in a Python library called “faKy” .
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|5th Multidisciplinary International Symposium on Disinformation in Open Online Media, MISDOOM 2023
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S. Barres Hamers, & Ceolin, D. (2023). FaKy: A feature extraction library to detect the truthfulness of a text. In Multidisciplinary International Symposium on Disinformation in Open Online Media (pp. 29–44). doi:10.1007/978-3-031-47896-3_3