Supervised Sentiment Analysis of Twitter Handle of President Trump with Data Visualization Technique

Abstract

The approval rating of the President of the United States (POTUS) can be used to gauge public support for the current administration. Public support, in turn, is highly dynamic and erratic, and can be influenced by current events, including political/economic policy announcements, ongoing scandals, treatment in the media, and general propaganda. The current POTUS, Donald Trump, is unique because, for the first time, the office of POTUS has direct access to social media platforms that offer a direct avenue of communication with the general population. Can the social media presence of POTUS influence the public approval of the administration? In this paper, we analyze the relationship between tweets generated by POTUS and his approval rating using sentiment-analytics and data visualization tools. The twitter feed of POTUS is mined, cleaned, and given a quantitative measure based on word content, called the “sentiment score”. By comparing tweets before the election, between election and inauguration, and after the inauguration, we find that the sentiment score for Mr. Trump's feed has increased on average with time by a factor of 60%. Using cross-correlation analysis, we find a preliminary causative relationship between POTUS twitter activity and approval rating. The findings provide a new perspective on the forces that influences public opinion, and the general strategy can be used for other analyses in the future.