Sentiment Analysis of TikTok User Comments on Student Proposal Hearing Videos - Lestari, Mugi; Vera (Communication In Research And Publications, 2025)
The rapid growth of social media has transformed digital platforms into spaces for public communication and audience interaction, including the dissemination of academic content. TikTok, as a form of digital broadcasting media, enables users to actively respond to various types of content through comments, creating rich linguistic data that reflect audience attitudes and perceptions. However, studies examining audience sentiment toward academic activities, particularly student proposal hearing videos on TikTok, remain limited, especially from a linguistic and broadcasting perspective. This study aims to analyze the sentiment and linguistic patterns of TikTok user comments on a student proposal hearing video to understand audience responses to academic content in digital media. The research employed a quantitative descriptive approach using sentiment analysis and frequency-based linguistic analysis. Data were collected from public TikTok comments through automated web scraping, followed by text preprocessing, word frequency analysis, n-gram analysis, and sentiment classification using an Indonesian RoBERTa-based transformer model. The results indicate that neutral sentiment dominates the comment section, followed by positive sentiment, while negative sentiment appears minimally. Linguistic patterns derived from word frequency and n-gram analysis reveal that audience responses are characterized by supportive, motivational, and evaluative language, emphasizing encouragement, smooth communication, and a positive academic atmosphere. These findings suggest that TikTok functions not only as a digital broadcasting platform for academic content but also as a participatory space where audiences construct collective and supportive discourse around academic experiences.