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Research on digital literacy literature: Topic mining and evolutionary analysis

领域(数学) 数据科学 过程(计算) 内容分析 读写能力 遗传(遗传算法) 计算机科学 数字化转型 主题模型 万维网 社会科学 社会学 情报检索 教育学 生物 生物化学 数学 纯数学 基因 操作系统
作者
Tao Zhang,Zheng Li,Ying Qi
出处
期刊:Journal of Librarianship and Information Science [SAGE]
标识
DOI:10.1177/09610006241309645
摘要

The paper employs text analysis techniques to conduct a systematic quantitative analysis of literature in the field of digital literacy, aiming to recognize and organize the research topics and their evolutionary process within this field. The study selected literature data on digital literacy from the Web of Science database between 2004 and 2023 as research subjects, dividing them into 10 stages. Subsequently, the LDA2vec method was used to recognize research topics in the field of digital literacy, and the evolutionary process of these topics was analyzed from two aspects: the evolution of topic content and the evolution of topic intensity. The results indicate that scholars in the field of digital literacy primarily focus on research topics such as education, digital technology, digital practice, and cybersecurity. The research process of these topics can be summarized into three stages: exploration, practice, and expansion. In terms of the evolution of topic content, the identified types of evolution include division, merging, inheritance, disappearance, and generation. In the aspect of topic intensity evolution, it was found that changes in topic intensity are influenced by factors such as policy, research content, and the primary field of study. In the future, the topic of education and digital technology will remain the focus of research in the field of digital literacy. At the same time, the field will concentrate on conducting in-depth research into social topics such as health, aging society, and the challenges and risks associated with digital transformation.
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