Code-Switching Among Saudi Influencers in Social Media: A Case Study Toward Documenting Patterns of Arabic Diglossia
Abstract This study investigates code-switching patterns among Saudi influencers on social media platforms, specifically Snapchat and X (formerly Twitter), to document aspects of Arabic diglossia. Employing a descriptive methodology, the research observed the posts and snaps of six Saudi influencers over a one-month period, analyzing their use of Standard Arabic (SA) and Saudi Dialect (SD) in various contextual situations. Findings reveal that the choice between SA and SD is primarily influenced by stance, audience, and persona, rather than a clear distinction between platforms. influencers tend to employ SA in serious, logical, and scientific discourse, while SD is predominantly used for humor, sarcasm, and jest, irrespective of the platform’s modality (written on X or oral on Snapchat). Nevertheless, a secondary pattern suggests a general inclination for SD use on Snapchat and SA on X among most influencers. Code-switching, predominantly from SA to SD, frequently occurs to address specific topics (e.g., sports), attract younger audiences, engage in humor, accommodate interlocutors, or simplify relative pronouns, with the latter being a universal practice across all influencers’ Snapchat content. Interestingly, when speakers opt for SA on Snapchat, their speech rate is notably slower than when using SD. Furthermore, specific personae, such as (MR) and (SAS), consistently utilize SA due to their self-presentation as a religious/conservative figure and a highly professional journalist, respectively. This research highlights the dynamic and context-dependent nature of code choice and code-switching in Saudi social media discourse.
Institutions
- Imam Mohammad ibn Saud Islamic University (SA)
Publication Details
- Journal
- Zenodo (CERN European Organization for Nuclear Research)
- Published
- 2026-01-14
- DOI
- https://doi.org/10.5281/zenodo.17764058
- Primary Topic
- Digital Communication and Language
- Type
- article
- Field-Weighted Citation Impact
- 0.00