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Usage frequency and application variety of research methods in library and information science: Continuous investigation from 1991 to 2021

arXiv 2606.31081 ↗First posted 30 Jun 2026cs.DL cs.CL cs.IRcited by 0

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Abstract (arXiv)

The present study analyzed over 26,000 research articles published between 1991 and 2021 in twenty-one major LIS (Library and Information Science) journals, using the machine learning (ML) approach to categorize the research methods used by LIS scholars. The findings of this study are significant. Firstly, there has been a shift in the research strategy from conceptual research (e.g., "Theoretical approach") to empirical research (e.g., "Interview") in LIS investigations over the past 31 years. Secondly, the research topics explored by LIS scholars during this period have moved from system-centered issues (e.g., "Information retrieval/models and algorithms") to user-centered topics (e.g., "Information services "). Thirdly, the study revealed dynamic and revealing relationships between the 18 research topics identified in the study and the 16 research methods commonly adopted in the LIS field. These dynamic relationships can be visualized by year and longitudinally via an interactive map created in this study.

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References · 12

  1. 2016XGBoost: A Scalable Tree Boosting Systemcited by 5,166
  2. 2014Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translationcited by 4,057
  3. 2019SciBERT: A Pretrained Language Model for Scientific Textcited by 1,414
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  10. 2015A Sensitivity Analysis of (and Practitioners' Guide to) Convolutional Neural Networks for Sentence Classificationcited by 92
  11. 2020Example-Driven Intent Prediction with Observerscited by 26
  12. 2020HINT3: Raising the bar for Intent Detection in the Wildcited by 21

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