Extending the knowledge base of foresight: The contribution of text mining

Victoria Kayser and Knut Blind

Technological Forecasting and Social Change, 2017, vol. 116, issue C, 208-215

Abstract: While the volume of data from heterogeneous sources grows considerably, foresight and its methods rarely benefit from such available data. This work concentrates on textual data and considers its use in foresight to address new research questions and integrate other stakeholders. This textual data can be accessed and systematically examined through text mining which structures and aggregates data in a largely automated manner. By exploiting new data sources (e.g. Twitter, web mining), more actors and views are integrated, and more emphasis is laid on the analysis of social changes. The objective of this article is to explore the potential of text mining for foresight by considering different data sources, text mining approaches, and foresight methods. After clarifying the potential of combining text mining and foresight, examples are outlined for roadmapping and scenario development. As the results show, text mining facilitates the detection and examination of emerging topics and technologies by extending the knowledge base of foresight. Hence, new foresight applications can be designed. In particular, text mining provides a solid base for reflecting on possible futures.

Keywords: Foresight; Text mining; Data analysis; Roadmapping; Scenario development; Big data (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (29)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:116:y:2017:i:c:p:208-215

DOI: 10.1016/j.techfore.2016.10.017

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