Abstract
Due to recent events in world politics, fake news, or malevolently established media has taken a major role in world politics discouraging the opinion of the people. There is a great impact of fake news on our modern world as it enhances a sense of discretion among people. Various sectors like security, education and social media are intensely researching in order to find improvised methods to label and recognize fake news to protect the public from disingenuous information. In the following paper, we have conducted a survey on the existing machine learning algorithm which is deployed to sense the fake news. The three algorithms used are Naïve Bayes, Neural Network and Support Vector Machine (SVM). Normalization is used to cleanse the information before implementing the algorithm.
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Utkarsh, Sujit, Azeez, S.N., Darshan, B.C., Chaya Kumari, H.A. (2021). A Study on Discernment of Fake News Using Machine Learning Algorithms. In: Suma, V., Bouhmala, N., Wang, H. (eds) Evolutionary Computing and Mobile Sustainable Networks. Lecture Notes on Data Engineering and Communications Technologies, vol 53. Springer, Singapore. https://doi.org/10.1007/978-981-15-5258-8_60
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DOI: https://doi.org/10.1007/978-981-15-5258-8_60
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