Prompting with Respect: Cultural Norms and User Experience in LLM Interactions
Abstract
Despite growing interest in prompt engineering, its influence on user experience—particularly in relation to cultural communication norms—remains largely unexplored. This controlled experiment examined how respectful versus directive prompting—a culturally meaningful contrast in Korean—affects Korean users’ psychological experience during LLM interactions. Forty-three Korean female college students were randomly assigned to respectful prompt (RP) (using polite requests, compliments, and gratitude) or directive prompt (DP) (using imperatives, criticism, and performance-based penalties) conditions. Participants completed a writing task using ChatGPT. Results indicated that RPs yielded significantly higher satisfaction, particularly for affinity and likability, whereas the difference in perceived output quality was smaller and nonsignificant. Furthermore, RPs elicited socially supportive ChatGPT responses, whereas DPs were followed by apologies, suggesting bidirectional social adaptation between users and ChatGPT. Together, these findings suggest that culturally grounded communicative conventions may shape users’ subjective experience even where perceived output quality does not differ significantly, pointing to culturally adaptive large language model systems that recognize diverse communication patterns as essential design considerations rather than imposing universal paradigms.