A Comprehensive Survey on Information Diffusion Models for Social Media Text

Abstract

People use social media platforms like Facebook, Twitter, and blog sites for expressing their views and criticising the products purchased and movies watched. They use these platforms for getting information like blood donation requirements and job opportunities. During the disastrous situations like floods and earthquakes, these platforms act as powerful media for passing messages to all people. During this COVID-19 pandemic period, all social media platforms are effectively used by all businesses for the instant communication and interactions between the groups of people. In all these scenarios, the information gets diffused and reaches different levels of people. Sometimes this diffusion gives positive aspects to the readers; sometimes it creates negative impacts to them, which has its own cascading effects. It becomes essential to monitor the rate of flow of information and stop spreading the fake or false messages. The application of suitable graph network modelling and theories would support this research issue and recommend the appropriate model for the social media data.