A Review and Analysis on Predicting Psychotic behaviors of Social Media Posts using Recurrent Neural Networks

Social media platforms have become an integral aspect of everyday life for individuals worldwide, with a usage rate of over 72% among adults. Nevertheless, the utilization of social media can exert detrimental effects on one's mental well-being. Social media platforms offer a convenient and efficient means of communication for individuals with mental disorders. Lately, there has been considerable interest in using machine learning (ML) approaches to explore mental health by analyzing large amounts of social media data. We aim to systematically review and analyze research trends predicting psychotic behaviors in social media posts using recurrent neural networks (RNNs). Many argue that some of these negative effects are not a direct cause of social networking; however, social media has increased the risk for these tendencies. We focus on a few of the negative effects to explain social media's impact on our lives, sometimes without us even knowing it, and we also propose some social media use to improve mental health. Research indicates a favorable correlation among elevated levels of anxiety, depression, suicide attempts, and heightened utilization of social media. In addition, 77% of participants indicated modifying their behaviors due to using social media.