Digital platforms like Instagram have become essential venues for the negotiation of language and identity, with the interplay of global and local practices vividly illustrated through the phenomenon of code-switching. This study seeks to fill a significant gap in comparative sociolinguistics by examining the motivations for code-switching between English and local languages in India (Hinglish) and Vietnam (Vietlish). By analyzing around 280 Instagram captions and comments, the study employs a multi-scalar framework that integrates micro-level textual mechanics, meso-level interactional dynamics, and macro-level sociocultural forces. This approach is critically informed by Translanguaging and Enregisterment, explicitly treating the blends as single, fused linguistic repertoires and is also informed by Critical Discourse Analysis, the sociolinguistics of globalization, and Auer’s insights into code-switching as a conversational resource. Our core finding reveals a distinct divergence: Hinglish emerges as a well-established and standardized system featuring its own grammar and recognized social functions, while Vietlish presents itself as a more fluid and evolving repertoire, strategically employed to evoke modernity, emotional resonance, and promotional appeal through the Algorithmic Audience mechanism. Utilizing Myers-Scotton’s markedness model, the research argues that this divergence is rooted in different processes of localization. Users in both contexts exhibit sophisticated semiotic strategies when navigating the “caption-hashtag-comment ensemble,” yet their linguistic choices reflect unique socio-historical trajectories shaping their digital language ecologies. This study contributes a novel comparative framework for theorizing digital language practices, establishing the Stabilized versus Emergent Continuum and demonstrating that the assimilation of global linguistic resources goes beyond mere borrowing, representing a dynamic process of sociocultural reconstruction.
Doley et al. (Fri,) studied this question.