Science, Technology & Innovation Textual Data – Oriented Topic Analysis and Forecasting: Model and A Case Study

Publication Type:
Conference Proceeding
Citation:
2014
Issue Date:
2014-11-27
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Not only the external quantities, but also the potential topics of current Science, Technology & Innovation (ST&I) are changing all the time, and their induced accumulative innovation or, even, disruptive revolution, should be able to heavily influence the whole society in the near future. Addressing and predicting the changes, this paper proposes an analytic method (1) to cluster associated terms and phrases to constitute meaningful technological topics and (2) to identify changing topical emphases, the results of which we carry forward to present mechanisms to forecast prospective developments via Technology Roadmapping approaches. Furthermore, an empirical case study of Award data in the United States National Science Foundation Division of Computer and Communication Foundations is performed to demonstrate the proposed method and the resulting knowledge could hold interests for R&D management and science policy in practice.
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