Research on the Theoretical Core and Driving Factors of Library Statistics Based on Large Language Models
Statistical work is an important tool for improving library management and also contributes practical references for the construction of library science theory.This study conducted a comprehensive search of academic papers related to library statistics from 1957 to 2024 in CNKI,selecting 508 highly relevant documents,utilizing large language models for full-text information extraction,and analyzing the core themes,theoretical core,and driving factors addressed in the relevant research literature.The research found that the themes of library statistics research have gradually shifted from a macro direction to a micro focus,delving into specialized studies such as user profiling,reading promotion,situational awareness,and collaborative services.The theoretical core of library statistical work mainly draws from theories in management,economics,and statistics,such as New Public Service Theory,Public Value Theory,and Cost-Benefit Theory.The study suggests that current library statistics research has issues with a lack of depth in the theoretical core and insufficient depth in specialized studies.In the future,library statistics should further refine specialized research,optimize management processes,and improve service quality to meet the needs of modern library governance and promote sustainable development of the library industry.
Library statisticsLarge language modelGenerative artificial intelligence
NETL
NSTL
万方数据
