Textile and Apparel Industries

Understanding Fashion in the Metaverse: A Topic Modeling Approach

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Abstract

The purpose of this study was to explore dominant topics about fashion associated with the metaverse discussed on Twitter through a topic modeling approach. A total of 187,510 tweets that contained four keywords (i.e., fashion, clothing, wearable, and apparel) in conjunction with the term “metaverse” were crawled for three years. After cleaning and preprocessing, 38,165 unique words were extracted from 84,742 tweets. Two stages of topic analyses were performed: Latent Dirichlet Allocation and the Gibbs Sampling Dirichlet Multinomial Mixture model. The data were understood best when classified into 16 topics with the four key building blocks of the metaverse. This study provided meaningful insights for the fashion communication literature through an empirical analysis of topics and themes expressed on Twitter. This study offered practical insights to understand the public's interests in fashion brands’ marketing strategies and types of digital fashion products sold in metaverse platforms and supporting services.

How to Cite:

Shin, E. & Miller, C., (2024) “Understanding Fashion in the Metaverse: A Topic Modeling Approach”, International Textile and Apparel Association Annual Conference Proceedings 80(1). doi: https://doi.org/10.31274/itaa.17562