Information Retrieval Model for Social Media Applications

Abstract

Social networks are rich source of data to analyze user habits in all aspects of life. User’s behaviour is decisiv e component of a health system in various countries. Promoting good behaviour can improve the public health signif icantly. In this work, we develop a new model for social network analysis by using text analysis approach. We defi ne each user reaction to global pandemic with analysing his online behaviour. Clustering a group of online users w ith similar habits, help to find how virus spread in different societies. Promoting the healthy life style in the high risk online users of social media have significant effect on public health and reducing the effect of global pandemic. In this work, we introduce a new approach to clustering habits based on user activities on social media in the time of pandemic and recommend a machine learning model to promote health in the online platforms.