M.S. AAI Capstone Chronicles 2024

Detecting Fake News Using Natural Language Processing Raza S, Ding C. (2022, Jan 30) Research Paper: Fake news detection based on news content and social contexts: a transformer-based approach. Int J Data Sci Anal. 2022;13(4):335-362. doi: 10.1007/s41060-021-00302-z. Epub 2022 Jan 30. PMID: 35128038; PMCID: PMC8800852. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8800852/ Ribeiro, M., Singh, S., & Guestrin, C. (2016). “Why should I Trust You?”: Explaining the predictions of any classifier. Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations . https://doi.org/10.18653/v1/n16-3020 Sangani, Raj (2021, Nov 11) Article: Interpreting and LSTM through LIME https://towardsdatascience.com/interpreting-an-lstm-through-lime-e294e6ed3a03 Sivasankari, S, and Vadivu, G. (2021, July 21) Article: Tracing the fake news propagation path using social network analysis. https://link.springer.com/article/10.1007/s00500-021-06043-2 Szczepanski, Mateusz, et al. (2021, Dec 08) Article: New explainability method for BERT-based model in fake news detection. https://www.nature.com/articles/s41598-021-03100-6

Staudemeyer, R. C., & Morris, E. R. (2019). – Understanding LSTM – a Tutorial into Long Short-Term Memory Recurrent Neural Networks .

University of Victoria, Dataset: The ISOT Fake News Dataset

24

49