Covid-19 Infodemic – Understanding Content Features in Detecting Fake News Using a Machine Learning Approach
Vimala Balakrishnan (Corresponding Author),
Hii Lee Zing,
Eric Laporte
Abstract:The use of content features, particularly textual and linguistic for fake news detection is under-researched, despite empirical evidence showing the features could contribute to differentiating real and fake news. To this end, this study investigates a selection of content features such as word bigrams, part of speech distribution etc. to improve fake news detection. We performed a series of experiments on a new dataset gathered during the COVID-19 pandemic using Decision Tree, K-Nearest Neighbor, Logistic Reg… Show more
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