In recent years, events are continuously discussed on Social Media in the form of status updates, posts, discussions and comments by its participants, volunteers, and supporters. Social media content generated before, during, and after an event could add valuable insight into success and popularity of an event. It can also generate ideas for future improvement of the event. With the fast evolving nature of Social Media, current events' Social Media content is ignored, forgotten, and overlooked for new sets of future posts, discussions, and comments. In our research, we believe that any publically available Social Media data can be captured and analyzed to produce some meaningful information. In this research, we are building a rating system through a combination of multiple sentiment analysis models using SM data.