• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Big-data Analytics: Exploring the Well-being Trend in South Korea Through Inductive Reasoning


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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Cite this article

[IEEE Style]
Y. Lee, M. Kim and S. Hong, "Big-data Analytics: Exploring the Well-being Trend in South Korea Through Inductive Reasoning," KSII Transactions on Internet and Information Systems, vol. 15, no. 6, pp. 1996-2011, 2021. DOI: 10.3837/tiis.2021.06.003.

[ACM Style]
Younghan Lee, Mi-Lyang Kim, and Seoyoun Hong. 2021. Big-data Analytics: Exploring the Well-being Trend in South Korea Through Inductive Reasoning. KSII Transactions on Internet and Information Systems, 15, 6, (2021), 1996-2011. DOI: 10.3837/tiis.2021.06.003.