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

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  • Kayser, Victoria
  • Blind, Knut

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.

Suggested Citation

  • Kayser, Victoria & Blind, Knut, 2017. "Extending the knowledge base of foresight: The contribution of text mining," Technological Forecasting and Social Change, Elsevier, vol. 116(C), pages 208-215.
    • Handle: RePEc:eee:tefoso:v:116:y:2017:i:c:p:208-215
    DOI: 10.1016/j.techfore.2016.10.017
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    References listed on IDEAS

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