The Korean Movie Minari: A Big Data Analysis

Abstract

The ultimate goal of this paper is to analyze 42 articles of Google regarding the Korean movie Minari. As a research tool for our goal, we used the software package NetMiner. A major point to note is that one word has the highest frequency (1,247 tokens) and the highest proportion (57.8%). More specifically, it occurs 1,247 times in 42 articles of Google. A further point to note is that topic 11 is the most occurred one in 40 articles, followed by topic 3, topic 4, and topic 10, in that order. When it comes to the use of keywords in 42 articles, the word film is the most widely used one, followed by the word Minari, the word family, the name Jacob, and the name Monica, in that order. Talking about degree centrality, the word family has the highest degree centrality, followed by the name Monica, the word Minari, and the word film, in that order. It is worthwhile noting, on the other hand, that the word family has the highest closeness centrality since the distance among the word family and the other words is the closest. Finally, this paper argues that the name Monica has the highest Eigenvector centrality since it has the most neighbors. Thus, the name Monica counts as the most influential and important.