A Smart Model to Detect Hindi Fake News for Social Media Platform using Hybrid Deep Learning - Barpha, Vidhya; Nair, Pramod S. (International Journal of Intelligent Systems and Applications in Engineering, 2023)
As a direct result, erroneous information spreads on those platforms very easily and quickly, leading to improper behaviours and outcomes. Sometimes individuals deliberately spread this erroneous information to upset others in order to advance their own objectives. Due to the rapid expansion of digital news, false information has already created severe hazards to the public's true judgment and trustworthiness. With the growing usage of social networking sites, which provide a fertile environment for its development and transmission, fake news has already put the public at tremendous risk. They made an effort to discover which algorithm was the most effective by contrasting the models they used. According to the results, the naive bayes algorithm may achieve accuracy of 83%, which is maximum. False news worsens the problem it already faces since it harms society as a whole in addition to the negative consequences it has on individuals. Due to the widespread dissemination of erroneous information, the "balance of the news ecosystem" may be upset.