Estimation of the 2020 US Presidential Election Competition and Election Stratagies

Abstract

The 2020 US presidential election is still more than a year away, but the media is noisy due to the continuous registration of candidates that will face Trump in the election. Trump has already started to check is rivals through media. So far, Joe Biden and Bernie Sanders seem to have to most possibility to face Trump in the election. Sensitivity analysis was conducted to the data collected from Twitter from the year 2019. The positivity scores have been proved to effect approval ratings, they are estimated to effect the likeliness of becoming the most popular candidate. The data was compared to the past election from 2008, 2012, and 2016. The elections included the past rival background of Obama and McCain, Obama and Romney, Trump and Clinton to show how positive ratings effect the election. Tweets were collected through HTML and Python. The collected data was analyzed using SPSS and MS Excel. Data was defined into three major statuses; positive, negative, and neutral by a lexicon named Valence Aware Dictionary and Sediment Reasoner (VADER). The null hypothesis was rejected through Independent Sample T-Test, Mann-Whitney U Test, Kruskal Wallis Test to show the difference between means. Research results show who will become Trump's estimated competitor for the 2020 election.