Will This Idea Spread Beyond Academia? Understanding Knowledge Transfer of Scientific Concepts across Text Corpora

Hancheng Cao, Mengjie Cheng, Zhepeng Cen, Daniel McFarland, Xiang Ren


Abstract
What kind of basic research ideas are more likely to get applied in practice? There is a long line of research investigating patterns of knowledge transfer, but it generally focuses on documents as the unit of analysis and follow their transfer into practice for a specific scientific domain. Here we study translational research at the level of scientific concepts for all scientific fields. We do this through text mining and predictive modeling using three corpora: 38.6 million paper abstracts, 4 million patent documents, and 0.28 million clinical trials. We extract scientific concepts (i.e., phrases) from corpora as instantiations of “research ideas”, create concept-level features as motivated by literature, and then follow the trajectories of over 450,000 new concepts (emerged from 1995-2014) to identify factors that lead only a small proportion of these ideas to be used in inventions and drug trials. Results from our analysis suggest several mechanisms that distinguish which scientific concept will be adopted in practice, and which will not. We also demonstrate that our derived features can be used to explain and predict knowledge transfer with high accuracy. Our work provides greater understanding of knowledge transfer for researchers, practitioners, and government agencies interested in encouraging translational research.
Anthology ID:
2020.findings-emnlp.158
Volume:
Findings of the Association for Computational Linguistics: EMNLP 2020
Month:
November
Year:
2020
Address:
Online
Editors:
Trevor Cohn, Yulan He, Yang Liu
Venue:
Findings
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1746–1757
Language:
URL:
https://aclanthology.org/2020.findings-emnlp.158
DOI:
10.18653/v1/2020.findings-emnlp.158
Bibkey:
Cite (ACL):
Hancheng Cao, Mengjie Cheng, Zhepeng Cen, Daniel McFarland, and Xiang Ren. 2020. Will This Idea Spread Beyond Academia? Understanding Knowledge Transfer of Scientific Concepts across Text Corpora. In Findings of the Association for Computational Linguistics: EMNLP 2020, pages 1746–1757, Online. Association for Computational Linguistics.
Cite (Informal):
Will This Idea Spread Beyond Academia? Understanding Knowledge Transfer of Scientific Concepts across Text Corpora (Cao et al., Findings 2020)
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PDF:
https://aclanthology.org/2020.findings-emnlp.158.pdf