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Mapping the evidence-based landscape in Chinese library and information science: a mixed-methods assessment

JunLing Ye et al.

Information Research2026https://doi.org/10.47989/ir31iconf64159article
AJG 1
Weight
0.50

What the paper says

Introduction. This study systematically explores the thematic distribution, evolutionary trajectory, and future directions of evidence-based research in the Library and Information Science (LIS) discipline in China. Method. A mixed-method design was employed, combining quantitative and qualitative approaches. Data were collected from 18 core CSSCI LIS journals (1999–2025). Methods included word frequency analysis, LDA topic modelling, and qualitative content analysis, with independent coding by two researchers to ensure reliability. Analysis. Thematic and evolutionary analysis was conducted using LDA topic modelling at an optimal k=9, evaluated through perplexity and coherence metrics. Content analysis was performed to identify application dimensions of evidence-based systems in LIS research. Results. The study identifies nine major research topics and reveals a clear shift from traditional, resource-centered themes to strategic, intelligence-aided, and application-oriented research. Evidence-based systems function through five key dimensions: perspective introduction, theoretical support, methodological innovation, diverse evidence integration and expansion of application scenarios. Conclusion. Evidence-based research in Chinese LIS has evolved significantly, showing strong local adaptation and interdisciplinary integration. To enhance future development, it is essential to develop a more comprehensive understanding of evidence-based research, give higher-level attention to evidence-based research, and explore wider horizons and application spaces for its implementation.

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https://doi.org/https://doi.org/10.47989/ir31iconf64159

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@article{junling2026,
  title        = {{Mapping the evidence-based landscape in Chinese library and information science: a mixed-methods assessment}},
  author       = {JunLing Ye et al.},
  journal      = {Information Research},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.47989/ir31iconf64159},
}

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Mapping the evidence-based landscape in Chinese library and information science: a mixed-methods assessment

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

† Text relevance is estimated at 0.50 on the detail page — for your query’s actual relevance score, open this paper from a search result.