Sentiment Analysis of TikTok Reviews for Strengthening Digital Marketing Strategies in Culinary MSMEs - Safira, Difa Anindya; Nur Anggraini, Amanda Devi; Marsally, Silvia Van; Mevadianti, Ersya (Universitas Multi Data Palembang, 2026)
This study aims to analyze the sentiment of TikTok user reviews as a basis for evaluating the digital marketing strategy of the culinary MSME Dapoer Barru. The scope of the study focuses on audience responses to three categories of TikTok content, namely product content, storytelling content, and humanized brand/BTS content. The method employed is lexicon-based sentiment analysis, incorporating text preprocessing stages. The data were obtained through comment scraping from three TikTok contents with the highest engagement levels, resulting in 3,235 comments, of which 491 units of text containing sentiment were further analyzed. The results indicate that negative sentiment is slightly more dominant than positive sentiment, with varying sentiment distributions across content categories. Storytelling content tends to generate higher positive sentiment, while humanized brand/BTS content is dominated by negative sentiment. These findings suggest that sentiment analysis can serve as an evaluative tool to support the strengthening of digital marketing strategies for culinary MSMEs based on audience responses.