Effects of the inter-Korean summit on the presidents of N. Korea, S. Korea, and the USA evaluated using sediment analysis and Twitter corpus
Abstract
Aim: This study aims to determine if and how online evaluations of North Korean, South Korean, and American presidents affect their respective countries’ public approval ratings.
Method: The HTML and Python programming languages were used to gather the tweets. SPSS and Microsoft Excel were used to analyze the data. An online lexicon and reasoning tool called Valence Aware Dictionary and Sediment Reasoner classified information as positive, negative, or neutral (VADER).
Findings: Independent Sample T-Test, Mann-Whitney U-Test, and Kruskal-Wallis Test were used to reject the null hypothesis of no significant difference between means. Despite popular belief, studies show that sediment score does not affect a show’s performance offline.
Implications/Novel Contribution: Since using sediment analysis to prove approval ratings is new, this study makes a significant contribution. Researchers have used sediment analysis to assess the link between the online and offline worlds. To ensure a steady data stream for future studies, we can predict who will be president next with our Estimating the next president analysis. Trump’s chances of being elected president in 2020 will be compared to Obama’s performance in office.
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