Big-data Analytics: Exploring the Well- being Trend in South Korea Through Inductive Reasoning
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, Younghan | - |
dc.contributor.author | Kim, Mi-Lyang | - |
dc.contributor.author | Hong, Seoyoun | - |
dc.date.accessioned | 2021-09-10T05:45:59Z | - |
dc.date.available | 2021-09-10T05:45:59Z | - |
dc.date.issued | 2021-06-30 | - |
dc.identifier.issn | 1976-7277 | - |
dc.identifier.issn | 1976-7277 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/sch/handle/2021.sw.sch/18759 | - |
dc.description.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. | - |
dc.format.extent | 16 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | 한국인터넷정보학회 | - |
dc.title | Big-data Analytics: Exploring the Well- being Trend in South Korea Through Inductive Reasoning | - |
dc.type | Article | - |
dc.publisher.location | 대한민국 | - |
dc.identifier.doi | 10.3837/tiis.2021.06.003 | - |
dc.identifier.scopusid | 2-s2.0-85109459351 | - |
dc.identifier.wosid | 000668543300003 | - |
dc.identifier.bibliographicCitation | KSII Transactions on Internet and Information Systems, v.15, no.6, pp 1996 - 2011 | - |
dc.citation.title | KSII Transactions on Internet and Information Systems | - |
dc.citation.volume | 15 | - |
dc.citation.number | 6 | - |
dc.citation.startPage | 1996 | - |
dc.citation.endPage | 2011 | - |
dc.type.docType | Article | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.description.journalRegisteredClass | kci | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Telecommunications | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.relation.journalWebOfScienceCategory | Telecommunications | - |
dc.subject.keywordPlus | OPPORTUNITIES | - |
dc.subject.keywordPlus | METHODOLOGY | - |
dc.subject.keywordAuthor | Apriori algorithm | - |
dc.subject.keywordAuthor | Big-data analytics | - |
dc.subject.keywordAuthor | Degree of visibility | - |
dc.subject.keywordAuthor | Inductive reasoning | - |
dc.subject.keywordAuthor | Keyword emergence map | - |
dc.subject.keywordAuthor | Well-being | - |
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