Quantifying Code-Switching in a Ukrainian Parliamentary Dataset 1990-2021
Proceedings of the ParlaCLARIN V Workshop on Interoperability, Multilinguality, and Multimodality in Parliamentary Corpora
Abstract
Analyzing code-switching – the practice of mixing multiple languages in one discourse – remains a significant task in natural language processing (NLP). This study examines the Ukrainian-Russian bilingual context, focusing on quantifying language alternation in a multilingual dataset. We introduce metrics to assess linguistic boundaries and patterns, specifically addressing the complexities of processing texts where Ukrainian and Russian are used interchangeably, including word-level hybridization. Using a corpus of approximately 200,000 tokens derived from parliamentary transcripts (1990-2021), we apply code-switching metrics to identify frequency and patterns of language use. Our findings provide insights into bilingual communication dynamics and can be used to improve language identification models for mixed-language data.