Data-Driven Evolution of Library and Information Science Research Methods (1990-2022): A Perspective Based on Fine-grained Method Entities
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Computer Science > Digital Libraries
Title:Data-Driven Evolution of Library and Information Science Research Methods (1990-2022): A Perspective Based on Fine-grained Method Entities
Abstract:Since the 1990s, advancements in big data and information technology have increasingly driven data-centric research in the field of Library and Information Science (LIS). To assess the influence of this data-driven research paradigm on the LIS discipline, this study conducts a fine-grained analysis to uncover the evolutionary trends of research methods within the domain. Using academic papers from LIS published between 1990 and 2022, four key categories of data-driven method entities are automatically extracted: algorithms and models, data resources, software and tools, and metrics. Based on these entities, the study examines the evolution of LIS research methods from three dimensions: the characteristics of research method entities over time, their evolution within different research topics, and the evolutionary features of research method entities across various research methods. The findings highlight data resources as a pivotal driver of methodological evolution in LIS, revealing a cyclical pattern of "emergence-stability/practical application" in the development of research methods within the field.
| Subjects: | Digital Libraries (cs.DL); Computation and Language (cs.CL); Computers and Society (cs.CY); Information Retrieval (cs.IR) |
| Cite as: | arXiv:2606.25320 [cs.DL] |
| (or arXiv:2606.25320v1 [cs.DL] for this version) | |
| https://doi.org/10.48550/arXiv.2606.25320
arXiv-issued DOI via DataCite (pending registration)
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| Journal reference: | Scientometrics, 2024 |
| Related DOI: | https://doi.org/10.1007/s11192-024-05202-0
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