Exploring Hype in Metaverse: Topic Modeling Analysis of Korean Twitter User Data

Abstract

Growing expectations and interest in the metaverse have increased the need to explore the public hype. This study measured the hype in the South Korean metaverse context and analyzed its temporal pattern. To this end, 129,032 tweets from Korean users who used the “metaverse” keyword were collected, and 86,901 tweets were analyzed. Using BERT-based topic modeling, a content analysis was performed. The extracted topics were classified into three expectation frameworks: specific expectations, generalized expectations, and frames. Our results imply that the pre-emptive inflation of expectations by the Korean government caused the public’s excessive expectations of the metaverse. Additionally, by using Twitter as a source for analyzing user-perceived hype, it was confirmed that the public responds to the expectations of other actors about the technology rather than expecting the technology itself. Furthermore, pronounced hype dynamics were observed by analyzing the distribution of topics over time.