Abstract
The topic modeling approach can indicate hidden relationships between articles in a particular academic discipline. This study aims to examine topics in library and information science (LIS) using the latent Dirichlet allocation method. From representative five journals, 1,648 full-text articles were analyzed. We labeled 30 identified topics based on the top 10 highly weighted terms for each topic, title, and body of articles. From the topic mapping, commonly used methods and shift of research issues in LIS were found.
| Original language | English |
|---|---|
| Pages (from-to) | 847-848 |
| Number of pages | 2 |
| Journal | Proceedings of the Association for Information Science and Technology |
| Volume | 55 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 2018 Jan 1 |
Keywords
- latent Dirichlet allocation
- library and information science research
- mapping
- Topic modeling
ASJC Scopus subject areas
- Computer Science(all)
- Library and Information Sciences
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Cite this
Kurata, K., Miyata, Y., Ishita, E., Yamamoto, M., Yang, F., & Iwase, A. (2018). Analyzing library and information science full-text articles using a topic modeling approach. Proceedings of the Association for Information Science and Technology, 55(1), 847-848. https://doi.org/10.1002/pra2.2018.14505501143