Linguistic Interplay on Social Media: Unraveling Indonesian-English Code Mixing on Twitter

Abstract

This qualitative descriptive study delves into the intricate realm of code mixing between Indonesian and English on the Twitter account known as Convomf. With a substantial following of over 1.3 million users, Convomf serves as a dynamic autobase forum where individuals express their concerns and experiences anonymously. This research is driven by two primary objectives: firstly, to categorize the distinct types of code mixing evident in the Convomf tweets, and secondly, to uncover the underlying reasons users engage in this linguistic practice. Employing a purposive sampling method, the study meticulously analyzed tweets collected between February and March 2023. The tweets selected for analysis were those that prominently featured code mixing, providing a rich dataset for examination. The methodology centered around the documentation of these tweets, followed by an in-depth analysis of the language patterns and structures used by the account holders. The findings of the study indicate a diverse array of code-mixing types, with six primary categories identified: insertion of a word (16%), phrase (22%), word reduplication (1%), clause (42%), hybrid constructions (9.5%), and idioms (9.5%). These variations demonstrate the complexity and versatility of code mixing as a linguistic strategy. Furthermore, the study explored the motivations behind code mixing, aligning with Hoffman's theoretical framework. The reasons range from discussing particular topics (65%) and clarifying speech (18.5%) to emphasizing certain points (15%), among others. Notably, interjections and repetition for clarification were also observed, albeit less frequently. Overall, this study contributes to the understanding of code mixing in digital communication on social media platforms. It reveals that code mixing is not only prevalent but also serves various communicative functions, reflecting the nuanced ways in which language is used in the context of social media. The insights gained from this research offer valuable implications for linguistics, particularly in the realm of bilingualism and language usage online.