Tackling the infodemic during a pandemic: A comparative study on algorithms to deal with thematically heterogeneous fake news

Tackling the infodemic during a pandemic: A comparative study on algorithms to deal with thematically heterogeneous fake news

Fake news poses a grave threat with devastating consequences in this information-centric age. While advances in data science undeniably hold the key to accurately detecting and curtailing the unfettered spread of fake news, guidance on the selection of algorithms and models that are best suited to a...

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Bibliographic Details
Main Authors:	Pramukh Nanjundaswamy Vasist, M.P. Sebastian
Format:	Article
Language:	English
Published:	Elsevier 2022-11-01
Series:	International Journal of Information Management Data Insights
Subjects:	Ensemble Fake news Machine learning Neural networks Text classification
Online Access:	http://www.sciencedirect.com/science/article/pii/S2667096822000763

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