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Identifying future trends by podcast mining: An explorative approach for Web-based horizon scanning

 
: Welz, Juliane; Riemer, Annamaria; Döbel, Inga; Dakkak, Nora; Schwartzenberg, Anna Sophie von

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Foresight 23 (2021), No.1, pp.1-16
ISSN: 1463-6689
ISSN: 1465-9832
English
Journal Article
Fraunhofer IMW ()
forecasting; content analysis; Future Trends; horizon scanning; Podcasting

Abstract
Purpose
The aim of this paper is to gain knowledge in podcast mining as an additional source for Web-based horizon scanning (HS). The paper presents theoretical insights on the potential of podcast mining by exploring topics, which may be relevant in the future, and by reflecting the results against a background of HS approaches. The study provides a preliminary overview by presenting an exemplary list of podcast shows for further research.
Design/methodology/approach
The paper uses an exploratory quantitative content analysis, which was conducted on the basis of 30 topics deemed to be relevant in the future and which were identified in the field of applied science. Based on these topics, podcasts and episodes were identified which address future-oriented topics and were discussed in term s of range of content.
Findings
The findings indicate that future-oriented topics are addressed in podcasts. However, differences in dynamics and range of content of the podcasts concerned highlight the necessity of identifying a list of suitable podcasts according to the specific scanning focus and the dynamics of each future-oriented topics.
Originality/value
While a growing number of podcast studies have already noted the importance of podcasts as a key medium, for example, educational processes and media sciences, no detailed explanation of podcast mining as a tool for the purposes of HS has been published. The review therefore makes an original contribution to this field, highlighting areas where future research is needed.

: http://publica.fraunhofer.de/documents/N-621219.html