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Framing Alcohol as Everyday: Network and Semantic Analysis of Sulbang on Korean YouTube
Jeong Kyu Lee1, Yifan Wang2, Mengqi Du2
1Department of Health and Exercise Science, University of Oklahoma.
Objective:
This study examines how sulbang (drinking broadcast) content on Korean YouTube contributes to alcohol normalization by analyzing structural organization, thematic framing, and audience engagement patterns.
Method:
We analyzed 1,012 sulbang-related videos using computational methods including channel networks, keyword co-occurrence clustering via CONCOR analysis, and semantic network mapping of user comments. Data collection involved YouTube scraping videos with over 50,000 views and algorithmically recommended content, with transcripts generated using automatic speech recognition.
Results:
Analysis revealed a highly centralized network dominated by mainstream entertainment channels (tvN ENT, MBC, JTBC) receiving algorithmic amplification. Keyword clustering identified six thematic domains embedding alcohol within everyday narratives of food, relationships, leisure, and emotional expression rather than featuring it prominently. Semantic analysis of viewer comments demonstrated parasocial engagement patterns, with audiences using relational language ("older sister," "friend") alongside alcohol-related terms.
Conclusion:
Sulbang normalizes alcohol consumption through subtle embedding within emotionally resonant, culturally familiar contexts amplified by platform algorithms rather than explicit promotion. These findings expose critical regulatory gaps in digital alcohol marketing and indicate the importance of comprehensive policy frameworks addressing influencer-driven content on social media platforms.
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