Code-mixing between Arabic and English among Jordanians on social media
Year: 2025
Type: article
Abstract: This study aims to investigate the types and motivations of code-mixing between Arabic and English in Jordanian social media conversations. Employing both quantitative and qualitative methods, the research examines fifteen recorded videos from various social media platforms like Facebook, Instagram, and YouTube. Instances of code-mixing are categorized using Muysken’s classification, which includes insertional, congruent lexicalization, and alternational types. The findings indicate that insertional code-mixing is the most prevalent, accounting for 80% of instances. This is followed by congruent lexicalization at 18.8% and alternational code-mixing at 1.2%. The study reveals that Jordanians frequently mix English into Arabic conversations, influenced by several factors such as social status, prestige, globalization, rapid advances in technology and artificial intelligence (AI), and education level. The study recommends incorporating code-mixing awareness into educational programs and encourages further research to explore the long-term effects of code-mixing on language development.
Source: Cogent Social Sciences
Language: English
Subfield: Linguistics and Language
Field: Social Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $1,165
OpenAlex ID: W4409829865