Quantifying the driving factors for language shift in a bilingual region.

Area of Science:

• Computational Linguistics
• Sociolinguistics
• Mathematical Modeling

Background:

• Global language endangerment is a significant concern, with many minority languages threatened by language shift.
• Existing large-scale monitoring of language shift relies on mathematical models, primarily differential equations, which average spatial data.

Observation:

• This study introduces a novel language dynamics model using cellular automata/agent-based principles, integrating detailed empirical data.
• This agent-based model allows for tracking language dynamics across both space and time, unlike differential equation models that average spatial information.
• Cellular automata models are applicable in complex scenarios, such as dispersed languages or 'language islands,' where differential equation models may fail.

Findings:

• Empirical data from a bilingual Austrian region demonstrates that direct interaction among speakers of the same language is the primary driver of language spread and retreat.
• External factors, such as bilingual education or religious institutions, exert a comparatively minor influence on language dynamics.

Implications:

• The proposed agent-based model provides a more granular understanding of language shift, capturing local changes in language use.
• This approach enhances the study of language endangerment and preservation strategies by highlighting the critical role of intra-speaker communication networks.