2023-11-14
FaKy: A feature extraction library to detect the truthfulness of a text
Publication
Publication
Presented at the
5th Multidisciplinary International Symposium on Disinformation in Open Online Media, MISDOOM 2023 (November 2023), Amsterdam, The Netherlands
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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| , , , | |
| doi.org/10.1007/978-3-031-47896-3_3 | |
| Lecture Notes in Computer Science | |
| The eye of the beholder: Transparent pipelines for assessing online information quality | |
| 5th Multidisciplinary International Symposium on Disinformation in Open Online Media, MISDOOM 2023 | |
| Organisation | Human-Centered Data Analytics |
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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 |
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