Analyzing User Sentiment Toward the New TikTok Go Feature in Indonesia

Ulwan Habib Ismail, Dini Turipanam Alamanda

Abstract


This study aims to analyze user sentiment toward the new TikTok Go feature in Indonesia using a descriptive quantitative approach based on social media sentiment analysis. The data were obtained from 335 user comments on TikTok, Twitter, and Instagram discussing the TikTok Go feature, collected through web scraping techniques during the period from May to July 2025. The data analysis process involved several stages, including text preprocessing, sentiment classification, frequency analysis, keyword extraction using TF-IDF, and thematic analysis. The results show that the majority of user sentiment was negative (74%), followed by neutral sentiment (19%) and positive sentiment (7%). The dominant themes found in the comments included difficulties in accessing the TikTok Go feature (55%), challenges in gaining the required number of followers (44%), account violations (6%), and general questions related to the feature's mechanism (3%). The triangulation of data from multiple platforms reinforced the consistency of the findings. These findings highlight the importance of more transparent and educational communication strategies to support the adoption of digital innovation. It is recommended that TikTok simplify the feature activation process and clarify technical requirements in order to enhance user experience and increase the successful adoption of TikTok Go in Indonesia.


Keywords


Sentiment Analysis, Sosial Media, Innovation Adoption, User Experience.

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DOI: https://doi.org/10.17509/ijdb.v5i1.83068

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