Federated Learning in Detecting Fake News: A Survey

Abstract

Due to technological advancements, social media usage has increased a lot resulting in a huge spread of fake information and false news among users of different languages. To reduce the spread of fake information, there is a need to detect the fake/false information being posted on social media apps like Twitter, Facebook, Instagram, and many. In order to identify false news, researchers employ models based on machine learning, natural language processing, and deep learning. These models are to be trained initially by huge amounts of data so that the models can gain knowledge from the trained data and predict the output for the new data provided. This study performs a detailed systematic review on different recent federated learning models being proposed for detecting fake news. It provides a detailed comparison of recently published articles related to fake-news detection using federated learning in terms of models they used. This study also provides different datasets which can be used in detecting fake-news using federated learning.