Sentiment analysis to predict election results using Python
Farha Nausheen, Sayyada Hajera Begum · 2018 2nd International Conference on Inventive Systems and Control (ICISC) · 2018
Sentiment analysis is an evaluation of the opinion of the speaker, writer or other subject with regard to some topic. In US presidential election 2016, Donald Trump, Hillary Clinton and Bernie Sanders were among the top election candidates. The opinion of the public for a candidate will impact the potential leader of the country. Twitter is used to acquire a large diverse data set representing the current public opinions of the candidates. The collected tweets are analyzed using lexicon based approach to determine the sentiments of public. In this paper, we determine the polarity and subjectivity measures for the collected tweets that help in understanding the user opinion for a particular candidate. Further, a comparison is made among the candidates over the type of sentiment. Also, a word cloud is plotted representing most frequently appearing words in the tweets.