Analisis Sentimen Kolom Komentar TikTok akun @holopis.com terhadap Isu Kekerasan Anak di Daycare Yogyakarta - Anindya Faisa Putri Wiyandina; Royyan Dhaydhabban; Gladis Kinanthi Herdyana Putri; Ardini Dyah Puspitaningtyas; Antony Caprio Russy Merang (CV. ITTC INDONESIA, 2026)
The transition of childcare functions to daycares in urban areas has created widespread public anxiety due to cases of child abuse. This study aims to analyze the distribution of public sentiment on TikTok regarding the child abuse case at a daycare in Yogyakarta using text mining methods. Data collection was conducted via web scraping using the Zeeschuimer extension, yielding a corpus of 505 user comments from a viral video. Data was analyzed computationally using Orange Data Mining. The results show a total dominance of negative sentiment at 93.85% (474 comments), with a heavy concentration below a score of 10 (86.93%). Neutral sentiment accounted for 3.56% (18 comments), and positive sentiment sat at 2.57% (13 comments). Theoretically, the TikTok comment section functions as a digital pillory, where netizens collectively enforce moral sanctions. This study proves that new media algorithms can shift personal anxiety into a massive public agenda that demands legal accountability.