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Finding correlation between fake news and correspondingsentiment analysis

Abstract

Detection of misinformation has become of great relevance and importance in the past few years. A significant amount of work has been done in the field of fake news detection using natural text processing tools combined with many other filtering algorithms. However, these studies lacked to observe any possible connection that might exist between the tone of the news and the validity of it. In order to research this field and find any existent correlation, my project addresses the potential role that sentiment associated with the news plays in identifying its validity. I perform sentiment analysis on tweets through natural language processing and use neural networks to train the model and test its accuracy.

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