Journal
TECHNOLOGICAL FORECASTING AND SOCIAL CHANGE
Volume 105, Issue -, Pages 179-191Publisher
ELSEVIER SCIENCE INC
DOI: 10.1016/j.techfore.2016.01.015
Keywords
Topic analysis; Technological forecasting; Text mining; Text clustering; Technical intelligence
Categories
Funding
- Australian Research Council (ARC) [DP140101366]
- National High Technology Research and Development Program of China [2014AA015105]
- US National Science Foundation [1527370]
- Direct For Social, Behav & Economic Scie
- SBE Off Of Multidisciplinary Activities [1527370] Funding Source: National Science Foundation
Ask authors/readers for more resources
The number and extent of current Science, Technology & Innovation topics are changing all the time, and their induced accumulative innovation, or even disruptive revolution, will heavily influence the whole of society in the near future. By addressing and predicting these changes, this paper proposes an analytic method to (1) cluster associated terms and phrases to constitute meaningful technological topics and their interactions, and (2) identify changing topical emphases. Our results are carried forward to present mechanisms that forecast prospective developments using Technology Roadmapping, combining qualitative and quantitative methodologies. An empirical case study of Awards data from the United States National Science Foundation, Division of Computer and Communication Foundation, is performed to demonstrate the proposed method. The resulting knowledge may hold interest for R&D management and science policy in practice. (C) 2016 Elsevier Inc. All rights reserved.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available