Please use this identifier to cite or link to this item: https://doi.org/10.1002/ffo2.17
Title: Extracting scenario archetypes with a quantitative text analysis of documents about the future
Authors: Alessandro Fergnani
Mike Jackson
Keywords: scenario archetypes, futures method, foresight method, scenario planning, quantitative text analysis, sentiment analysis, futures of work
Issue Date: 24-Feb-2019
Publisher: Wiley
Citation: Alessandro Fergnani, Mike Jackson (2019-02-24). Extracting scenario archetypes with a quantitative text analysis of documents about the future. Futures & Foresight Science e17. ScholarBank@NUS Repository. https://doi.org/10.1002/ffo2.17
Rights: Attribution-NonCommercial 4.0 International
Abstract: We propose a scenario planning method that combines quantitative text analysis with the creation of scenario narratives. We design a variation in the scenario archetypes method (Dator, Journal of Futures Studies, 14, 1–18, 2009), a futures method to create four archetypal scenarios based on four predetermined generic alternative futures named continued growth, collapse, discipline, and transformation. In our variation, we extract archetypal information on the futures from documents about the future via quantitative text analytic techniques, and qualitatively elaborate this information into comprehensive narrative scenarios. This method can harness the abundance of unstructured textual data, significantly reducing the time employed to collect the relevant building block information to write scenarios without decreasing the scenarios’ quality. On the contrary, the text analytic algorithm we use allows us to identify very rich and archetype‐specific information. We present the result of an application of this method in a case study on the futures of work. The method's contributions to the futures literature and limitations are discussed.
Source Title: Futures & Foresight Science
URI: https://scholarbank.nus.edu.sg/handle/10635/164034
DOI: 10.1002/ffo2.17
Rights: Attribution-NonCommercial 4.0 International
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