<![CDATA[The rapid growth of social media platforms such as TikTok has generated large volumes of unstructured user comments, particularly on local content that attracts substantial public attention, including Gorontalo-related videos. This situation requires efficient data-collection methods to support the systematic analysis of public responses. This study aims to develop a TikTok comment-scraping procedure by utilizing the Google Colab cloud platform integrated with the Apify scraping service and Python programming. This research employs an applied descriptive approach, which includes configuring the cloud environment, executing the TikTok Scraper Actor, extracting the scraping results in JSON format, converting them into CSV files, and validating the dataset using the Pandas library. The findings indicate that the procedure successfully extracted comments from two viral Gorontalo-themed TikTok videos and produced a structured dataset suitable for public-response analysis. Moreover, the use of Google Colab proved effective for conducting large-scale scraping without the limitations of local hardware. This study contributes a standardized, efficient, and easily replicable methodological model for social-media-based research in Indonesia.]]>
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