Analysis of Code-Mixing Found in YouTube Content - Tsuraya, Rifda Ghaitsa; Haryanto, Sigit (Universitas Muhammadiyah Surakarta, 2024)
Purpose: This study examines code-mixing in YouTube content created by Indonesian YouTubers Jesselyn Lauwreen, Gita Savitri Devi, and Sandy Kristian Waluyo, focusing on the types and motivations behind their language use. Methodology: Adopting a qualitative descriptive approach, the research uses content analysis to collect and categorize instances of code-mixing. Data collection began with selecting and transcribing relevant videos to capture spoken content, which was then organized into tables for analysis. Code-mixing was categorized into three types: insertion, alternation, and congruent lexicalization. Results: The reasons for code-mixing were analyzed, including discussing specific topics, quoting, showing emphasis, and expressing group identity. Applications/Originality/Value: The findings reveal that insertion is the most frequent type of code-mixing across all three YouTubers, followed by alternation and congruent lexicalization. The primary reason for code-mixing was talking about a particular topic, with expressing group identity also being significant.