메뉴 건너뛰기
.. 내서재 .. 알림
소속 기관/학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
로그인 회원가입 고객센터 ENG
주제분류

추천
검색
질문

논문 기본 정보

자료유형
학술저널
저자정보
Jong-Hwa Lee (Dong Eui University) Hoanh-Su Le (University of Economics and Law, VNU-HCM) Hyun-Kyu Lee (Pukyong National University)
저널정보
한국인터넷전자상거래학회 인터넷전자상거래연구 인터넷전자상거래연구 제19권 제5호
발행연도
2019.10
수록면
1 - 15 (15page)
DOI
10.37272/JIECR.2019.10.19.5.1

이용수

표지
📌
연구주제
📖
연구배경
🔬
연구방법
🏆
연구결과
AI에게 요청하기
추천
검색
질문

초록· 키워드

오류제보하기
Based on a study of the wheel of emotions of American psychologist Plutchik (1980). The emotional wheel of Plutchik’s has seven adjectives: surprised, sad, happy, fearful, disgusted, bad, angry. And the emotions were grouped in a hierarchical manner. We have reconstructed the English - based emotional wheel with Korean language processing and use it for the analysis of the emotion of the netizen in various media based on text. Media on the web environment was collected from textual informal data such as Internet news, article comments, blogs, and social network services (SNS) content (Facebook, Twitter, Instagram, YouTube, etc.). We collected the emotion words from the hash tags of SNS and constructed the Korean emotion dictionary based on the seven emotion sets of Flickr. In this study, we have obtained over 150,000 Korean emotional words in seven dimensions then calculated the weight of emotional words in each dimension. In other words, we want to find emotion index through cluster analysis. PVClust is an R package for evaluating uncertainty in hierarchical cluster analysis. For each cluster of hierarchical clustering, the quantity called p-value is computed through multi-scale bootstrap resampling. The p-value is a value between 0 and 1, and it is possible to check how strong the data is supported in the cluster, and it is expected to be utilized as a basic research on building three-dimensional emotional DNA through emotional word ranking in each emotional dimension.

목차

Abstract
Ⅰ. Introduction
Ⅱ. Literature Review
Ⅲ. Research Method
Ⅳ. Analysis and Results
Ⅴ. Conclusion
References

참고문헌 (23)

참고문헌 신청

함께 읽어보면 좋을 논문

논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!

이 논문의 저자 정보

이 논문과 함께 이용한 논문

최근 본 자료

전체보기

댓글(0)

0