Exploring the topic structure and evolution of associations in information behavior research through co-word analysis

Shengli Deng, Sudi Xia, Jiming Hu*, Hongxiu Li, Yong Liu

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

Abstract

This study aims to reveal the distribution of topics, and the associations among them, in information behavior research from 2009 to 2018. Working with a collection of 6744 publications from the Web of Science database, co-word analysis is used to investigate the overall topic structure, the associations among the topics, and their evolution in different years, which is supplemented by visualization with science maps. The results uncovered an unbalanced distribution of topics, and that the topics cluster into six communities representing subdivisions of this field: information behavior in patient-centered studies; information interaction in the digital environment; information literacy in health and academic contexts; health literacy on the Internet; information behavior in child-centered studies; and information behavior in medical informatics. The findings supplement and provide refinements to work on the state of this field, and help researchers obtain an overview of the past decade to guide their future work.

Original languageEnglish
JournalJOURNAL OF LIBRARIANSHIP AND INFORMATION SCIENCE
DOIs
Publication statusE-pub ahead of print - 2020
MoE publication typeA1 Journal article-refereed

Keywords

  • co-word analysis
  • Information behavior research
  • topic evolution
  • topic structure

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