The popularity of social networks make them most efficient to integrate into the Emergency Management process. Posts on social networking sites can help people by ensuring timely detection of an emergency. Often during the situations of a natural disaster, there is an information chasm created between the affected and the unaffected area that further compounds the confusion and chaos. In this paper, we examine the various challenges that exist while attempting to integrate social networks and Emergency Management and trace the state-of-art techniques that exist in various domains that come together for this Emergency Management system. We propose an end-to-end framework that takes public posts from social networking sites and converts it into a structured format that makes the information actionable. A summarization technique may be applied to the acquired information post mining of social media feed to convert everything into a text message that can be released into various social platforms. To increase the reach of this post and to warrant better public participation in the crisis in a timely manner, we apply influence maximization techniques and monitor the diffusion process of this generated post through a diffusion modelling technique that we propose. We conduct experiments to analyze the performance of this model and of the influence maximization process and conclude with an analysis of the experiments and the observed results and list out improvements that we intend to incorporate in future versions of this work. © 2019 IEEE.