Predicting Federal Election result using Sentiment Analysis

We want to predict the result of the federal election in Canada using the sentiment of the people tweeting on Twitter using Sentiment Analysis. The federal elections have been talk of the town with which candidate winning the elections. We are already aware of the results that Justin Trudeau won the elections but we want to have a model, which analyses the sentiment of the people based on what people have been posting about the candidates. We want to show the entire lifecycle of data analysis starting from first collecting the data, cleaning the tweets that have been fetched by utilizing various strategies like removing emoticons, stop words and etc.. The process of feature engineering will also be incorporated in the project. The project will also demonstrate various data mining techniques as well as the Natural language processing techniques. After collecting all the tweets and cleaning them the next step has to be to determine which candidate have been getting more positive or negative tweets and then predcting the result using the suitable model. The outcome needs to be visualized in the form of bar charts, pie charts or heat maps. The entire project depends on how the outcome is displayed to the end user so any visualization platform can be used to achieve the same.