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딥러닝에 의한 여흥과학: 지역사회언어학을 중심으로Entertainment Science Based on Deep Learning: Focused on Areal Sociolinguistics

Other Titles
Entertainment Science Based on Deep Learning: Focused on Areal Sociolinguistics
Authors
노형남
Issue Date
2017
Publisher
한국사회언어학회
Keywords
entertainment science; deep learning; areal sociolinguistics; Bob Dylan; Coelho
Citation
사회언어학, v.25, no.1, pp.27 - 52
Indexed
KCI
Journal Title
사회언어학
Volume
25
Number
1
Start Page
27
End Page
52
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/86066
DOI
10.14353/sjk.2017.25.1.02
ISSN
1226-4822
Abstract
The aim of this paper is to suggest a new scientific discipline in sociolinguistic research, dealing with entertainment science based on deep learning focused on areal sociolinguistics as a current methodology de facto made by ultra-fusion of area studies and sociolinguistics. From a fact-oriented and data-oriented analysis perspective this paper examines real phenomena of areal sociolinguistics provoked by two famous sing-a-song writers: America’s Robert Allen Zimmerman, so-called 2016 Nobel prize winner Bob Dylan, and Brazil’s Paulo Coelho de Souza. The results of the qualitative analyses between two eminent areas, where particular attributes of alternative societies are filled with swarm intelligence on the basis of resistance consciousness, suggest the areal sociolinguistics mentioned-above. From the diachronic and synchronic viewpoints of cross-over geographical cultures this paper makes a mid-range generalization, on making a definition about alternative societies in America and Brazil in spite of the geographical methodology of area studies between the two countries, being offered by stubborn resistance against ready-made ideas to calm down keen psychological conflicts among established moral principles to overcome philosophical catastrophe in social chaos, and full of competitive instinct against existing generations.
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