•  
  •  
 

Scientific Information Research

Keywords

ancient book large language models, dropout behavior, psychological resilience, large language model users, technical resilience

Abstract

[Purpose/significance]The deep integration of ancient book digitization and large language models is the future development trend. In order to clarify the influence factors and formation mechanisms of dropout behavior among users of domain ancient book large language models, mobilize the willingness of users to use large language models, achieve high-quality user retention, and promote the non-human high-quality development of domain large language models. [Method/process]This study takes users in the field of ancient books as an example, based on resilience theory, and draws on grounded theory research methods to code and deconstruct first-hand data obtained from in-depth interviews with 30 users of ancient book large language models. The focus is on extracting influencing factors and conceptual categories from the perspective of resilience theory, and then constructing a research model on the mechanism of dropout behavior formation among users of ancient book large language models from the perspective of resilience theory. [Result/conclusion]The research results show that resilience factors, psychological resilience, cognitive factors, and situational factors are important factors affecting the dropout behavior of users of the ancient book large language model.Resilience factors include three dimensions:information resilience, technological resilience, and environmental resilience. Psychological resilience mainly goes through three stages: emotional stress, emotional resilience, and cognitive resilience.The research results provide necessary reference for effectively preventing users of ancient language models from dropout and achieving high-quality user retention.

Digital Object Identifier (DOI)

10.19809/j.cnki.kjqbyj.2025.02.005

Download

Share

COinS