A political landscape of any country has always been complex in nature, this complexity can be attributed to several factors such as number of parties, policies and most importantly mixed public sentiment. The rise of social media has given people all around the world to converse and debate with a very large audience, the sheer amount of exposure a tweet or a post received is unprecedented. Recent development in the field of deep learning has led to its usage in several different verticals. Techniques like LSTM allow for performing a sentiment analysis of the posts. This can be used to predict the overall sentiment of the masses in relation to a political party or an individual. Several studies have shown how to approximately predict public opinion, such as in political elections, by analyzing user activities in blogging platforms and on-line social networks. Machine learning has a dramatic growth in recent years and it has been applied in every technology from self-driving cars to e health sectors. We proposed a machine learning models to predict the chances of the winning the upcoming election based on the user or supporter opinions on the social media platform. In Social media the supporter or user express their opinion or feedback post for their favorite’s party or opposite party. We have to collect the text posts regarding the election and political campaigns, then we have created the machine learning models to predict the results.
CITATION STYLE
JayaKumar, S., Patel, P., Singh, R. K., Shivraj, & Paul, A. (2019). Election result prediction using deep learning techniques. International Journal of Engineering and Advanced Technology, 8(4), 74–77.
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