The Analysis of Code-Mixing in Abel Cantika’s Instagram Captions

Abstract

This research discusses the phenomenon of code-mixing in beauty influencer Abel Cantika's Instagram caption reels. The purpose of this study is to identify the types of code mixing used and analyze the reasons behind its use. This research uses a descriptive qualitative method with data in the form of 52 captions collected from September to December 2024. Data analysis was conducted based on Hoffmann's (1991) theory regarding the types and reasons for using code-mixing. The results showed that there were two types of code-mixing found, namely single element insertion (27 data) and partial or total phrase insertion (25 data). The most dominant type is single element insertion, especially beauty terms such as “shade”, ‘sunscreen’, and “comment”. The reasons for using code-mixing are divided into four, namely discussing certain topics (42 data), interjection (5 data), expression of group identity (3 data), and lack of vocabulary (2 data). The findings show that the use of code-mixing is not merely a language style but a communication strategy tailored to the audience, topic, and context of the digital platform. This research contributes to the understanding of bilingualism and language behavior in social media, especially in beauty-related content, and illustrates how language adapts to modern communication needs.