ABSTRACT
Digital and the quick expansion of social media (Facebook, Twitter, etc.) allowed for unprecedented information flow. Social media users create and disseminate inaccurate information due to its widespread use. False stories foster mistrust. It's difficult for a person to spot this misinformation. Even a specialist should explore several options before deciding on a topic's authenticity. Due to this issue, we built a machine-enabled machine learning method to identify fake news items. We devised several data processing strategies to train our model. We trained the machine using the object retrieval technique and model evaluation using those pre-processing approaches. Experimental testing shows that our false identification system outperforms individual diagnosis.
