Polymer science has enhanced human life for more than 100 years, and numerous scientific papers have been published in this field. In this study, we captured trends in polymer science by performing an automated analysis of the titles and abstracts of papers that contained the keyword “polymer” using topic-modeling techniques grounded in natural language processing (NLP). NLP-based topic models are promising tools for automatically extracting useful information from papers and other textual data in polymer science.
- Yoshifumi Amamoto
- Yoh-ichi Mototake
- Takaaki Ohnishi
