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All Journal ELITERATE : Journal of English Linguistics and Literature Studies
Wiraatmaja, Fajar Shakti
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Humanities Education Languange, Linguistic, Communication & Media

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AN ANALYSIS OF CODE MIXING USED BY BEAUTY INFLUENCER SHANIKA ON TIKTOK Sindy, Mutiara; Zed, Allysa Nurfitriani; Rizqi, Amelia Nur; Nurhaliza, Rahma; Wiraatmaja, Fajar Shakti; Rusyad, Maheza
ELITERATE : Journal of English Linguistics and Literature Studies Vol 5, No 2 (2026): ELITERATE : Journal of English Linguistics and Literature Studies
Publisher : Faculty of Languages and Literature, Universitas Negeri Makassar

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26858/eliterate.v5i2.87582

Abstract

This study examines the types of code-mixing employed by Shanika, a beauty influencer, in her TikTok videos and analyzes their distribution across her content. Based on Muysken's (2000) classification, which categorizes code-mixing into insertion, alternation, and congruent lexicalization, this study identifies the most prevalent type and explores how these patterns function within digital communication. Using a qualitative descriptive methodology, the analysis examines five video posts from Shanika's official TikTok account, covering hair care, fashion, and lifestyle. The findings indicate that insertion is the most frequently observed form, with 56 instances (65.1%), followed by congruent lexicalization with 16 instances (18.6%), and alternation with 14 instances (16.3%). The study suggests that Shanika predominantly inserts English lexemes into Indonesian grammatical structures to convey concepts related to beauty and fashion more accurately and effectively. The predominance of insertions reflects a strategic use of code-mixing by content creators to enhance audience engagement, project a contemporary image, and align with global trends in digital media. This study contributes to understanding code-mixing practices in digital communication in Indonesia and offers insights into how bilingual content creators reach multilingual audiences on social media platforms.
Co-Authors Nurhaliza, Rahma Rizqi, Amelia Nur Rusyad, Maheza Sindy, Mutiara Zed, Allysa Nurfitriani