A Large-Scale Sentiment Analysis of Tweets Pertaining To The 2020 US Presidential Election
Rao Hamza Ali, Gabriela Pinto, Evelyn Lawrie, Erik J. Linstead · Research Square · 2022
Abstract We capture the public sentiment towards candidates in the 2020 US Presidential Elections, by analyzing 7.6 million tweets sent out between October 31st and November 9th, 2020. We apply a novel approach to first identify tweets and user accounts in our database that were later deleted or suspended from Twitter. We present sentiment analysis of the presidential candidates across these identified posts alongside active ones, and share key insights. The aim is to highlight the importance of conducting sentiment analysis on all posts captured in real time, including those that are now inaccessible, in determining the true sentiments of the opinions around the time of an event.