<![CDATA[The growing complexity of digital communication has transformed hate speech practices on social media, particularly within multilingual societies where code mixing functions as a strategic resource for constructing implicit, concealed, and context-dependent meaning. This poses significant challenges for forensic linguistic analysis and legal enforcement, since offensive meaning is not always explicitly encoded at the surface level of language. This study aims to (1) identify the forms and patterns of code mixing in digital hate speech, (2) analyze its strategic functions in terms of meaning obfuscation, intensity regulation, and indirectness, and (3) examine its implications from forensic linguistic and legal perspectives. Employing a qualitative descriptive design with an interpretative approach, the study draws on code-mixed hate speech data collected from social media platforms, analyzed through an integrated framework combining sociolinguistics, pragmatics, discourse analysis, and forensic linguistics. The findings show that code mixing occurs systematically at the lexical, phrasal, and clausal levels, predominantly through insertion and alternation patterns; that it operates strategically to obscure meaning, regulate evaluative intensity, and convey hostility indirectly; and that its use produces semantic ambiguity and plausible deniability that complicate the identification of speaker intention and the classification of utterances as legitimate criticism or harmful speech. The study concludes that code mixing constitutes a deliberate discursive strategy with significant implications for forensic linguistic analysis and the regulation of hate speech in multilingual digital communication, offering practical value for law enforcement, forensic linguists, and content moderation system developers.]]>
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