딥러닝에 의한 여흥과학 ※ : 지역사회언어학을 중심으로

• 발행기관: 한국사회언어학회
• 저자명: 노형남
• 간행물 정보: 『사회언어학』제25권 1호, 27~52쪽, 전체 26쪽
• 주제분류: 어문학 > 언어학
• 파일형태: PDF
• 발행일자: 2017.03.30

영문 초록

Noh, Hyung-nam. 2017. “Entertainment Science Based on Deep Learning: focused on Areal Sociolinguistics”. The Sociolinguistic Journal of Korea 25(1). 27~52. 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.

목차

1. 서론

2. 이론적 배경

3. 딥러닝에 의한 여흥과학

4. 연구의 시사점

5. 결어

키워드

entertainment science deep learning areal sociolinguistics Bob Dylan Coelho