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Abstract
Abstract This study explores the grammatical variability of modal auxiliary verbs in English as a lingua franca. Focusing on the ongoing change must, have to, and need to, this research utilizes two spoken corpora: the Vienna–Oxford International Corpus of English (VOICE) and the Asian Corpus of English (ACE). A total of 4487 tokens of must, have to, and need to were analyzed using Bayesian mixed‐effects multinomial regression models. The findings reveal that lingua franca users exhibit more systematicity than inconsistency in their use of necessity modals across geographic and cultural borders. Speakers in ACE and VOICE show a preference for have to and need to when expressing necessity and obligation. Furthermore, the influence of linguistic and social factors is similar across Asian and European contexts. Our observations highlight the potential of Bayesian statistics for the study of lingua franca uses of English, which currently based on small digital corpora.
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