LDA Topic Modeling on the Trends of the Next Digital Generation on the New Internet Revolution, Metaverse

Abstract

The purpose of this study is to explore the trends of the Z and Alpha generation user groups on the metaverse for each unique topic by using LDA topic modeling based on big data analysis. This study seeks a new sustainability direction for the metaverse by discovering the internal and experiential value of users' experiences beyond the technical perspective of the metaverse. The worldwide enthusiasm for the metaverse was driven by the impact of the COVID-19 pandemic, technological advances in computer graphics and infrastructure, and the expansion of the digital generation user base such as generation Z and Alpha. Research on the metaverse has been increasing since 2021, but theoretical approaches by generational subgroups of nextgeneration digital users on the metaverse are still insufficient. Considering the timeliness of the research topic, this study subdivides the next-generation users into two groups, the Z generation and the Alpha generation, to discover the characteristics of each generation regarding the metaverse. In the process of analysis, the importance and relevance of words were identified by text mining analysis of unstructured big data. Next, through LDA topic modeling and visualization analysis, the meaning of each topic group was interpreted based on word pockets, which are related words that have mutually exclusive uniqueness for each topic. Python 3.10 and Textom 6 version software were used for analysis. This study will present meaningful academic and practical insights into the sustainability and utilization of the metaverse by a diverse user base. Keywords—Big data, Data mining, LDA Topic Modeling, Metaverse, Digital Generation