Is Human–LLM Interaction Culture-Dependent? A Cross-Linguistic NLP Analysis of Student Interviews on AI-Assisted Thesis Writing

Abstract

This study investigates whether human–LLM interaction in academic writing exhibits cross-cultural variation. Using NLP-informed corpus methods, we analyze nine semi-structured student interviews from three national contexts (Romania, Bulgaria, Switzerland) to examine how AI use is linguistically constructed across three dimensions of epistemic positioning: agency strength, authority dynamics, and discourse-level stance. Results show a strong predominance of distancing and hedging strategies, with AI consistently framed as a functional writing support tool rather than an epistemic authority. At the same time, modest but systematic cross-country differences indicate culturally embedded variation in how students discursively negotiate epistemic responsibility and evaluation in AI-assisted writing practices.

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