Applying LSA text mining technique in envisioning social impacts of emerging technologies: The case of drone technology

Heeyeul Kwon, Jieun Kim and Yongtae Park

Technovation, 2017, vol. 60-61, 15-28

Abstract: This research proposes a novel method of identifying and understanding the holistic overview of emerging technologies’ unintended consequences. Latent Semantic Analysis (LSA) text mining technique is employed to yield multiple groups of contextually similar terms from future-oriented data sources, comprising both experts’ and the public's concerns regarding future technologies. Resulting term clusters are considered as new abstractions, or so-called scenarios, of future social impacts. Furthermore, the study acquires greater depth and breadth in conceptualizing social impacts through considering condition- and value-related terms as key linking factors to previous social impact-related literature. Our proposed methodology seeks to gain insights into the utilization of future-oriented data sources for the foresight activity, hoping to mitigate public skepticism and pursue a better social acceptance of emerging technologies.

Keywords: Emerging technology; Drone; Foresight; Future-oriented data; Latent semantic analysis; Scenario; Social impact; Text mining (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (24)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:techno:v:60-61:y:2017:i::p:15-28

DOI: 10.1016/j.technovation.2017.01.001

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