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Journal : Journal of Authentic Research

Case Marking System and Language Creativity of Bima Language on Social Media TikTok: Sistem Penandaan Kasus dan Kreativitas Bahasa dalam Bahasa Bima di Media Sosial TikTok Ibrahim, Ibrahim; Arafiq, Arafiq; Aziz, Atri Dewi; Isnaini, Muh.
Journal of Authentic Research Vol. 4 No. 2 (2025): December
Publisher : LITPAM

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36312/ev0btp08

Abstract

This study examines the case marking system and linguistic creativity of the Bima language as used on TikTok, focusing on how grammatical variation and creative expression shape linguistic identity in digital spaces. The research employs a mixed-methods approach combining qualitative descriptive analysis and limited quantitative categorization to explore the frequency and form of case-marking patterns. The significance of this study lies in its contribution to understanding how regional languages adapt to new communicative environments while preserving their grammatical essence and sociocultural relevance in the digital era. The findings reveal that the Bima language on TikTok predominantly maintains a nominative–accusative alignment, though occasional ergative-like patterns appear in informal or elliptical utterances. Linguistic creativity manifests through processes such as code-mixing, word simplification, and stylistic innovation, illustrating how speakers negotiate identity and solidarity through digital discourse. These results imply that digital platforms like TikTok can function not only as spaces of linguistic experimentation but also as instruments for regional language revitalization and intergenerational transmission. Nevertheless, this study is limited by its scope, which focuses exclusively on a small sample of Bima TikTok users and does not include data from other platforms or face-to-face interactions. Future research should expand the dataset and incorporate sociolinguistic variables such as gender, education, and network size to capture a more comprehensive picture of language dynamics in online contexts.