Abstract
The era of Blockchain Technology (BT) and Machine Learning (ML) is dramatically improved in general, and particularly in the sense of human vision in the field of artificial intelligence. BT's leadership has been extended to a variety of fields that contribute to major advances in the artificial smart and machine network. Today, Fake News (FN) has become more and more popular. Due to the broad variety of free content, it is now easier than ever to generate and forge false information. Using BT with ML in FN detection makes it possible to produce a prediction system as well as broaden the scope of the classification of the news. This chapter introduces a survey of research papers on FN detection based on ML, and analyzes in terms of the database used, method and accuracy achieved. Moreover, it introduces a survey of research papers on FN detection based on BT, and analyzes in terms of some selected features. Finally, blueprint versions of the FN detection system have been introduced.
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Loey, M., Taha, M.H.N., Khalifa, N.E.M. (2022). Blockchain Technology and Machine Learning for Fake News Detection. In: Rawal, B.S., Manogaran, G., Poongodi, M. (eds) Implementing and Leveraging Blockchain Programming. Blockchain Technologies. Springer, Singapore. https://doi.org/10.1007/978-981-16-3412-3_11
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