Exploring the Buzz Surrounding Dress to Impress: Text Mining YouTube Comments on the Gamified Fashion Platform
(A2026-133645)

AUTHORS

Yunyu Chu, Oklahoma State University; Kyuree Kim, Oklahoma State University; Joseph Kim, Oklahoma State University

ABSTRACT

Dress to Impress (DTI), a virtual fashion styling game has gained substantial popularity among young consumers and has generated buzz across digital platforms. To understand the drivers behind its success, this study analysed the Dress To Impress Rewind: 2024 YouTube video’s user comment data to explore consumer perception of DTI gaming experiences and its community culture. YouTube user comments were collected and analysed using various text mining analysis techniques, including word frequency analysis, sentiment analysis, and semantic network analysis. Results revealed that popular YouTubers’ comments facilitated high engagement within the community, and nearly 64% of the comments showed a positive sentiment. Three central themes were identified from the comments: 1) Celebrating the success of DTI in 2024; 2) Spending and social interaction around in-game items; and 3) Nostalgic calls for past DTI content. Findings of the study illustrate how a comment section functions as an active community engagement.