코퍼스 기반 미국 TV 시리즈 장르별 언어 복잡성 분석:EFL 학습 자료 선정의 기준 탐색

Investigating content themes of American TV series for EFL learners through corpus analysis

This study investigates genre-based differences in linguistic complexity across three types of American TV series—animation for teens, comedy, and investigation–law—to provide empirically grounded criteria for EFL material selection. Ninety subtitle files (30 per genre) were compiled through diversified sampling and analyzed using the L2 Syntactic Complexity Analyzer and the Lexical Complexity Analyzer. Key syntactic indices, including clauses per sentence, compound noun phrases, and NP density, showed significant genre effects, with animation displaying the lowest clause density and NP complexity, whereas comedy and investigation–law exhibited higher structural density and greater NP expansion. Lexical indices such as lexical diversity and sophistication similarly distinguished the genres, with animation showing simpler lexical profiles and the other genres demonstrating richer and more specialized vocabulary. Correlation analyses further revealed clustering among density-based syntactic measures and inverse relations between length-based and density-based indices, indicating distinct internal complexity profiles. These findings offer quantitative evidence for matching genre-specific input to learner proficiency levels and contribute to corpus-informed discussions on optimizing linguistic input quality in media-based EFL learning. The results also demonstrate how corpus-driven metrics can clarify variation in authentic audiovisual input, supporting more principled decisions in the development of genre-sensitive learning resources for educators.