K-POP in BBC News: A Big Data Analysis

Abstract

The main goal of this paper is to analyze 40 pieces of BBC news broadcasted from 4th, 1, 2020 to 21st, 12, 2022 regarding K-pop. As a theoretical tool for this goal, we used the software package NetMiner. A point to note is that one word has the highest frequency (1,005 tokens) and the highest proportion (0.507). A further point to note is that in the word cloud, the noun BTS occurs as the biggest in size. This in turn implies that it is the most frequent one and thus it counts as the most significant. With respect to topics occurred in 40 pieces of BBC news, it is interesting to note that topic 1 was the most widely used one, followed by topic 8, topic 7, topic 2, and topic 9, in that order. Talking about major words occurred in 40 pieces of BBC news, the word BTS was the most occurred one, followed by the word fan, the word group, the word band, and the word year (the word member), in descending order. This paper argues, on the other hand, that the word BTS has the highest in-degree centrality (0.454545). This in turn indicates that the word BTS counts as the most significant or popular. This paper further argues that the word BTS has the highest in-closeness centrality (0.594310). More specifically, the distance among the word BTS and other nodes is the shortest, thereby counting as the most significant and important.