Applying LSA text mining technique in envisioning social impacts of emerging technologies: The case of drone technology |
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| Affiliation: | 1. School of Computer Science & Engineering, Soongsil University, 369 Sangdo-ro, Dongjak-gu, Seoul 156-743, Republic of Korea;2. Graduate School of Management of Technology, Sungkyunkwan University, 2066, Seobu-ro, Jangan-gu, Gyoenggi-do, 440-746, Republic of Korea;3. Department of Systems Management Engineering, Sungkyunkwan University, 2066, Seobu-ro, Jangan-gu, Gyoenggi-do, 440-746, Republic of Korea;1. Kyoritsu Women''s University, 2-2-1 Hitotsubashi, Chiyoda-ku, Tokyo 101-8437, Japan;2. Graduate School of Media and Governance, Keio University, 5322 Endo, Fujisawa-shi, Kanagawa 252-0882, Japan;3. Freelance;4. National Institute of Science and Technology Policy, 3-2-2 Kasumigaseki, Chiyoda-ku, Tokyo 100-0013, Japan;5. New Energy and Industrial Technology Development Organization, 1310 Omiya-cho, Saiwai-ku, Kawasaki-shi, Kanagawa 212-8554, Japan;1. Decision Systems & e-Service Intelligence Lab, Centre for Artificial Intelligence, Faculty of Engineering and Information Technology, University of Technology Sydney, PO Box 123, Broadway, NSW 2007 Sydney, Australia;2. School of Management and Economics, Beijing Institute of Technology, Beijing 100081, China;1. Center for Aviation Innovation Research (CAIR), The University of Tokyo, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8654, Japan;2. Graduate School of Innovation Management, Tokyo Institute of Technology, Japan |
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| 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. |
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| Keywords: | Emerging technology Drone Foresight Future-oriented data Latent semantic analysis Scenario Social impact Text mining |
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