Sabila, Dzihni Azka
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Affective Strategies in Arabic-Indonesian Code-Mixing on TikTok: A Discourse Analysis of Microlearning Content on the @hayfaacademy Account Sabila, Dzihni Azka; Sopian, Asep; Maulani, Hikmah; Yulia, Hana; Layla, Olivia Noufal
Mantiqu Tayr: Journal of Arabic Language Vol. 6 No. 1 (2026): Mantiqu Tayr: Journal of Arabic Language
Publisher : Institut Agama Islam Ma'arif NU (IAIMNU) Metro Lampung

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25217/mantiqutayr.v6i1.6946

Abstract

This study examines affective strategies expressed through Arabic-Indonesian code-mixing in Arabic microlearning content on TikTok. As an informal and participatory learning space, TikTok enables not only the delivery of instructional messages but also the creation of emotional, social, and cultural connections. This research aims to identify the types and roles of code mixing in videos from the @hayfaacademy account and analyze how these linguistic choices foster affective engagement between the creator and viewers. Using a qualitative approach with critical discourse analysis, the study explores macro structures of meaning, classifies forms of language mixing, and interprets viewers’ emotional involvement through the affective domain framework. The findings reveal that code mixing supports comprehension while strengthening interpersonal closeness, indicating its dual role as a linguistic and affective strategy within digital learning settings. Theoretically, this study contributes to discussions on affect in Arabic language learning, particularly within social media environments where emotions and meaning-making are intertwined. Practically, the results offer insights for educators and content creators on designing microlearning materials that are empathetic, culturally resonant, and accessible to diverse learners. Future studies may expand the scope by incorporating multimodal analysis and engaging participants from broader sociocultural backgrounds to deepen understanding of linguistic and affective dynamics in Arabic microlearning.