Twitter data based prediction model for influenza epidemic

These days controlling influenza outbreaks have become an important issue for health authorities. It causes millions of deaths worldwide so that, it must be controlled at an early stage. In this research work, we have done an associated study of algorithms and methods, modelling the outbreak of an epidemic with the focus of swine flu. In the introduction section we have given the significance of the study with respect to micro-blogging website Twitter. In related work we have a survey from different resources and ideas applied to predict and detect epidemics and studied the advantages and limitations of the model have been proposed previously. In the proposed work we have proposed our research work with a new idea of Swine Flu Hint Algorithm (SEHA), which look after epidemic activities happen on Twitter and we have used some techniques and models to build this framework.