Technological advancements have streamlined many daily activities, transforming consumer shopping behaviors. A significant shift from traditional in-person shopping to e-commerce platforms has occurred due to the convenience and user-friendly features of online shopping. There has been a discernible preference for e-commerce in Indonesia, with Shopee and Tokopedia leading the market. Projections indicate a sustained increase in e-commerce adoption within the country from 2019 to 2028. The Unified Theory of Acceptance and Use of Technology 3 (UTAUT3) provides a contemporary framework for understanding the factors influencing e-commerce adoption, such as consumer reviews. This study explores the efficacy of multiclass classification and topic modeling methods in discerning technology acceptance patterns within user reviews on Shopee and Tokopedia. Employing the IndoBERT model for multiclass classification yielded a trained model with approximately 99 accuracy. Conversely, Latent Dirichlet Allocation (LDA) for topic modeling achieved optimal coherence at a five-topic structure. The research compared these methods' capabilities to extract insights from a substantial corpus of user reviews, comprising 253,742 from Shopee and 251,859 from Tokopedia, utilizing the UTAUT3 model as an analytical lens.