Framing Alcohol as Everyday: Network and Semantic Analysis of Sulbang on Korean YouTube.

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 scraping YouTube videos with more than 50,000 views and algorithmically recommended content, and generating transcripts using automatic speech recognition.

RESULTS

Analysis revealed a highly centralized network, dominated by mainstream entertainment channels (tvN ENT, MBC, JTBC), that received algorithmic amplification. Keyword clustering identified six thematic domains that embed alcohol within everyday narratives of food, relationships, leisure, and emotional expression rather than prominently featuring it. Semantic analysis of viewer comments demonstrated parasocial engagement patterns, with audiences using relational language ("older sister," "friend") alongside alcohol-related terms.

CONCLUSIONS

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 underscore the importance of comprehensive policy frameworks that address influencer-driven content on social media platforms.