Big-data Analytics: Exploring the Well- being Trend in South Korea Through Inductive Reasoning
- Authors
- Lee, Younghan; Kim, Mi-Lyang; Hong, Seoyoun
- Issue Date
- 30-Jun-2021
- Publisher
- 한국인터넷정보학회
- Keywords
- Apriori algorithm; Big-data analytics; Degree of visibility; Inductive reasoning; Keyword emergence map; Well-being
- Citation
- KSII Transactions on Internet and Information Systems, v.15, no.6, pp 1996 - 2011
- Pages
- 16
- Journal Title
- KSII Transactions on Internet and Information Systems
- Volume
- 15
- Number
- 6
- Start Page
- 1996
- End Page
- 2011
- URI
- https://scholarworks.bwise.kr/sch/handle/2021.sw.sch/18759
- DOI
- 10.3837/tiis.2021.06.003
- ISSN
- 1976-7277
1976-7277
- Abstract
- To understand a trend is to explore the intricate process of how something or a particular situation is constantly changing or developing in a certain direction. This exploration is about observing and describing an unknown field of knowledge, not testing theories or models with a preconceived hypothesis. The purpose is to gain knowledge we did not expect and to recognize the associations among the elements that were suspected or not. This generally requires examining a massive amount of data to find information that could be transformed into meaningful knowledge. That is, looking through the lens of big-data analytics with an inductive reasoning approach will help expand our understanding of the complex nature of a trend. The current study explored the trend of well-being in South Korea using big-data analytic techniques to discover hidden search patterns, associative rules, and keyword signals. Thereafter, a theory was developed based on inductive reasoning - namely the hook, upward push, and downward pull to elucidate a holistic picture of how big-data implications alongside social phenomena may have influenced the well-being trend.
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Collections - College of Natural Sciences > Department of Leisure and Recreation > 1. Journal Articles
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