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

논문 기본 정보

자료유형
학술저널
저자정보
저널정보
영남중국어문학회 중국어문학 중국어문학 제76호
발행연도
2017.1
수록면
197 - 228 (32page)

이용수

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

초록· 키워드

오류제보하기
Zao-Yi's ≪OubeiShihua≫ is a representative poetry criticism in Qing Dynasty. The ≪OubeiShihua≫ consists of 12 volumes, and has selected ten representative poets of China and focused on their poetry. There are not only poets of Yuan, Ming, but also poets of Qing Dynasty poets in ≪OubeiShihua≫. In particular, Wu Wei-ye and Zha Shen-xing, who are only decades old than themselves, are discussed side-by-side with Li-Bai and Du-Fu. It was possible because of Zao-Yi's developing point of view on poetry. In this paper, I review the Qing poetry evaluation method mentioned in the text of ≪OubeiShihua≫ of Qing Dynasty poet. Because Zao-Yi lived in the middle of the Qing Dynasty, he clearly realized the rich and abundant information of Wu Wei-ye and Zha Shen-xing, the representative poets of Qing Dynasty living in front of him, as well as the characteristics of their works. Wu Wei-ye and Zha Shen-xing has lived in a different age by forty years away and has worked on different backgrounds ; in the age of a replacement of the dynasty and a stability of the dynasty respectively. This paper will show the clear characteristics of the works of Wu Wei ye and Zha Shen-xing more closely through the viewpoint of Qing’s intellectuals, and furthermore, this work will be the foundation for the study of Qing poetry. First, this paper examines the Zao’s poetic and his viewpoints on Qing poetry, and then examines poetry criticism of Wu Wei-ye and Zha Shen-xing represented in ≪OubeiShihua≫ Next, it analyze the evaluation methods in ≪OubeiShihua≫ with the aspects of 1) the author's age and growth background, 2) comparison of poetry and the historical research method.

목차

등록된 정보가 없습니다.

참고문헌 (18)

참고문헌 신청

함께 읽어보면 좋을 논문

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

이 논문의 저자 정보

최근 본 자료

전체보기

댓글(0)

0