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Horizon scanning in policy research database with a probabilistic topic model

Author

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  • Kim, Hyunuk
  • Ahn, Sang-Jin
  • Jung, Woo-Sung

Abstract

National governments take advantage of collective intelligence when conducting foresight processes. They grasp emerging issues through expert reviews as well as public opinions. It raises national agendas and affects policy-making process. Therefore, by examining policy papers which contain societal issues, we can perceive past, current, and future environments. In this study, we exploit policy research database of Republic of Korea, which is a unique source that automatically collects all policy papers written by national research institutes, to extract latent topics and their trends over 10 years through a probabilistic topic model. Detected topics fairly correspond to expert-selected future drivers in national foresight report, implying that public discourse and policy agenda are coupled. We suggest to utilize open government data and text mining methods for building open foresight framework that various actors exchange their opinions on societal issues.

Suggested Citation

  • Kim, Hyunuk & Ahn, Sang-Jin & Jung, Woo-Sung, 2019. "Horizon scanning in policy research database with a probabilistic topic model," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 588-594.
    • Handle: RePEc:eee:tefoso:v:146:y:2019:i:c:p:588-594
    DOI: 10.1016/j.techfore.2018.02.007
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    References listed on IDEAS

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    Cited by:

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    2. Ahn, Sang-Jin & Yoon, Ho Young & Lee, Young-Joo, 2021. "Text mining as a tool for real-time technology assessment: Application to the cross-national comparative study on artificial organ technology," Technology in Society, Elsevier, vol. 66(C).
    3. Pauliina Krigsholm & Kirsikka Riekkinen, 2019. "Applying Text Mining for Identifying Future Signals of Land Administration," Land, MDPI, vol. 8(12), pages 1-15, November.
    4. Choi, Hyunhong & Woo, JongRoul, 2022. "Investigating emerging hydrogen technology topics and comparing national level technological focus: Patent analysis using a structural topic model," Applied Energy, Elsevier, vol. 313(C).
    5. Ahn, Sang-Jin, 2020. "Three characteristics of technology competition by IoT-driven digitization," Technological Forecasting and Social Change, Elsevier, vol. 157(C).
    6. Zhang, Hao & Daim, Tugrul & Zhang, Yunqiu (Peggy), 2021. "Integrating patent analysis into technology roadmapping: A latent dirichlet allocation based technology assessment and roadmapping in the field of Blockchain," Technological Forecasting and Social Change, Elsevier, vol. 167(C).

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