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Evolution and diffusion of information literacy topics

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  • Yating Li

    (Central China Normal University)

  • Ye Chen

    (Central China Normal University)

  • Qiyu Wang

    (Central China Normal University)

Abstract

Investigation of the topic of information literacy and its changes can be informative for researchers and provide a better understanding of the corresponding domains. This study conducted a topic model dynamic analysis of the articles on information literacy studies in the Web of Science core collection database that were published from 2005 to 2019. The global topics and their popularities, topical similarities and correlations, along with the evolution of temporal local topics and the diffusion of subject local topics were analyzed and presented. Nine global topics differed in terms of their temporal and subject characteristics, and this study focused on ability, technology, field, people, place and application of information literacy. For the temporal local topics, crossing was the main evolutionary mechanism; hence, the core topic words were relatively stable, but few new research directions have been explored in recent years. For the subject local topics, absorbing with division and absorbing were the main mechanisms, which supported the diffusion progress of information literacy studies among subjects. However, it is necessary to promote the development of future research through the innovative development of multidisciplinary integration. Researchers and practitioners should focus on the impact of information technology, increase the breadth and depth of the research field, and develop innovative evaluation methods that are based on data to promote the comprehensive, sustainable and effective improvement in information literacy.

Suggested Citation

  • Yating Li & Ye Chen & Qiyu Wang, 2021. "Evolution and diffusion of information literacy topics," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 4195-4224, May.
    • Handle: RePEc:spr:scient:v:126:y:2021:i:5:d:10.1007_s11192-021-03925-y
    DOI: 10.1007/s11192-021-03925-y
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    References listed on IDEAS

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    2. Li, Jianhui & Ruan, Xinfeng & Zhang, Jin E., 2022. "The price of COVID-19-induced uncertainty in the options market," Economics Letters, Elsevier, vol. 211(C).

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