1. A data-driven analysis of the knowledge structure of library science with full-text journal articles
- Author
-
Giyeong Kim, Tatsawan Timakum, and Min Song
- Subjects
Trace (semiology) ,Content analysis ,Computer science ,020204 information systems ,05 social sciences ,0202 electrical engineering, electronic engineering, information engineering ,Library science ,02 engineering and technology ,0509 other social sciences ,Library and Information Sciences ,050904 information & library sciences ,Knowledge structure ,Data-driven - Abstract
In previous studies, full-text analyses and mining techniques have not been combined to identify and trace changes in the knowledge trends of library science over the past 20 years (1997–2016). Thus, to grasp the knowledge trends of library science at a fine-grained level, this study analyzes full-text journal articles from six top-ranked library science journals by applying text-mining techniques such as co-word analysis, text summarization, and topic modeling. Visualization tools were used to map the knowledge structure of library science. The findings indicate that, during the past 20 years, library science has developed into an interdisciplinary knowledge structure that integrates librarianship topics with a range of other fields, generating major topics that include the academic library, the digital library, research methodology, library marketing, information retrieval, digital information, document citation, and so on. In the past ten years, the library science discipline has focused increasingly on research methodology and evaluation and become more concerned with digital information management.
- Published
- 2018