Sentiment Analysis between VADER and EDA for the US Presidential Election 2020 on Twitter Datasets

Abstract

The 2020 US Election took place on November 3, 2020, the result of the election was that Joe Biden received 51.4% of the votes, Donald Trump 46.9%, and the rest were other candidates. The period before the election was a time when people conveyed who would vote and conveyed the reasons directly or through social media, especially Twitter through keywords or tags such as #JoeBiden & #DonaldTrump. In this paper, we will compare sentiment analysis and exploratory data analysis against US election data on Twitter. The overall objective of the two case studies is to evaluate the similarity between the sentiment of location-based tweets and on-ground public opinion reflected in election results. In this paper, we find that there are more "neutral" sentiments than "negative" and "positive" sentiments. This study are focused finding sentimental tweets that people say on twitter for both presidential candidate and The dataset used is from and provided by Kaggle and has been updated on November 18, 2020, it is hoped that we hope that the academic community, computational journalists and research practitioners alike can utilize our dataset to study relevant scientific and social problems.