<![CDATA[TikTok has become an influential space in which individual self-presentation, algorithmic visibility, religious norms, and local cultural identities are negotiated. This study aims to identify forms of norm-violating TikTok content associated with selected West Sumatran creators and interpret them through Islamic ethics and the Minangkabau framework of Sumbang Duo Baleh. It employed directed qualitative content analysis of a bounded, purposively selected corpus of publicly accessible videos, documented TikTok Live segments, captions, audiovisual features, and relevant comment threads uploaded during 2024-2025 and collected between February and June 2026. Data were documented digitally, coded through theory-informed and context-sensitive categories, and analyzed using the interactive stages of data condensation, data display, and conclusion verification. The findings identified three case-based clusters: coarse or sexually suggestive speech, including bacaruik; dance performances involving movement, dress, or visual framing considered inconsistent with selected standards of propriety; and sexually suggestive TikTok Live interactions. Islamic ethical analysis connected these practices with responsible speech, protection of dignity, modesty, and appropriate public interaction. Minangkabau cultural analysis related them to Sumbang Kato, Sumbang Pakai, Sumbang Mancaliak, Sumbang Bagaua, and Sumbang Duduak. Audience comments revealed competing interpretations rather than a uniform communal response. The study's originality lies in integrating two mutually reinforcing but analytically distinct normative frameworks: Islamic ethics emphasizes individual moral accountability, whereas Sumbang Duo Baleh adds contextual propriety and relational responsibility toward family, kin, and nagari. This study contributes a culturally situated framework for digital content analysis and supports the development of platform-aware, ethically responsible, and culturally sensitive digital literacy without claiming prevalence, creator motivation, algorithmic causation, or audience effects. It also identifies priorities for comparative, audience-based, and participatory future research.]]>
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