Executive Summary : | People use social media platforms like facebook, twitter and blog sites for expressing their views and criticising the products purchased, movies watched and so on. They also use these platforms for getting information like blood donation requirements, job opportunities, movie releases, cultural and sports events and so on. During the disastrous situations like flood, storm, earthquakes, and hurricanes, these platforms act as powerful media for passing messages to all kinds of people. During this Covid-19 pandemic period, all these social media platforms are effectively used by all types of business and services for the instant communication and interactions between the groups of people. As per the Alltheresearch report (www.alltheresearch.com/report/5/social-media-analytics-market) on the global social media analytics market for the period 2016-2023, Northern America dominated this market from the beginning whereas Asia-Pacific region started showing progress since 2021. The growth of social media analytics is used for brand promotion among the competitors. In all the above said scenarios, the information get diffused and reached different levels of people. Sometimes this diffusion gives positive aspect to the readers; sometimes it creates negative impact to them which has its own cascading effect. Hence, it becomes essential to monitor the rate of flow of information and stop spreading the fake or false message. The application of suitable graph network data modelling and theories along with Natural Language Processing (NLP) techniques would support this research issue and recommend the appropriate mathematical model for the social media data. |