DETECTING FAKE NEWS USING TEXT MINING

Digital misinformations is a significands problems for an enlightened societies outstanding to the fasted disseminations of misinformation’s which kinds it hard for manual verification to stayed ahead of the pace. In the paper “Detecting Counterfeit News Using Text Mining” an efficient and systematic approach to detecting information beaded on analyzing linguistic sand stylistic patterns in the bulletin articles texted is offered. This project has an accuracy of 89%. Through integrating text mining technology and machine learning-based classification, the program successfully separates truthful and fraudulent news articles according to the text patterns. The software developed enables users to squared the validity of news articles through a straightforward user interface. Although it cannot replace human intelligence, it can help enhance media literacy skills.

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