A Systematic Analysis of the Computational Intelligence Techniques for Fake News Detection

With the advent of social media platforms, the process of information dissemination has become quick and easy. The users have started creating and sharing news information of even the miner activities on the social media platforms. Some of the users also started dissemination the news without any factual information that misleads the legitimate users. The early detection of fake news is essential so that the misleading information does not influence the opinion of legitimate users towards any person or activity. The concept of fake news detection came to the attention from the last decade, especially after the 2016 US election. The researchers are continuously making efforts to detect fake news with novel techniques and by modifying the existing techniques to improve the classification performance. This research work presents the systematic analysis of the computational intelligence techniques for fake news detection. The analysis is performed by incorporating the quality contributions of recent years. Comprehensively, the analysis is described based on the effective techniques, datasets, and challenges in the field.