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Scenario development using web mining for outlining technology futures

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  • Kayser, Victoria
  • Shala, Erduana

Abstract

Scenario development is an established foresight method. However, scenario processes require much time and the integration of a balanced set of initial information (reports, expert interviews, etc.) remains a challenge. One of the key tasks in scenario development is to capture the topic and identify its key influences. This has potential for improvements. In times of big data, far more options exist for the rapid exploration of a topic than manual literature analysis. Hence, this work examines web and text mining for its usability in data retrieval and aggregation to improve scenario development. In this article, a new scenario process is proposed and described using the topic quantified self as an example. As the results show, web and text mining present a very good starting point for discussing the scenario content. The rapid overview with the visualizations remarkably reduces the reading effort. Still, future projections need to be searched manually, but the results from the automatic analysis comprehensively guide this step.

Suggested Citation

  • Kayser, Victoria & Shala, Erduana, 2020. "Scenario development using web mining for outlining technology futures," Technological Forecasting and Social Change, Elsevier, vol. 156(C).
    • Handle: RePEc:eee:tefoso:v:156:y:2020:i:c:s0040162520309124
    DOI: 10.1016/j.techfore.2020.120086
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    References listed on IDEAS

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    6. Yusuke Kishita & Takuma Masuda & Hidenori Nakamura & Kazumasu Aoki, 2023. "Computer‐aided scenario design using participatory backcasting: A case study of sustainable vision creation in a Japanese city," Futures & Foresight Science, John Wiley & Sons, vol. 5(1), March.

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