The Korean Association for the Study of English Language and Linguistics
[ Article ]
Korea Journal of English Language and Linguistics - Vol. 19, No. 4, pp.817-836
ISSN: 1598-1398 (Print)
Print publication date 31 Dec 2019
Received 01 Nov 2019 Revised 10 Dec 2019 Accepted 18 Dec 2019

딥러닝을 이용한 셰익스피어 작품의 감정 분석

서혜진 ; 이종현 ; 신정아*
제1저자, 동국대학교
공동저자, 서울대학교
*교신저자, 동국대학교
Sentiment analysis of Shakespeare’s plays using a deep learning technique
Seo, Hye-Jin ; Jonghyun Lee ; Jeong-Ah Shin*


This study examined the sentiment movement of Shakespeare’s plays (four tragedies and five comedies) using a deep learning technique. Sentiment analyses have been used in several fields to extract aspects of opinions using sentiment dictionaries such as ANEW, AFFINE, and VADER, which involve an evaluation of a word list for sentiment analysis. Nowadays, however, as deep learning algorithms develop, it became possible to conduct a sentiment analysis by using deep learning algorithms. This study directly compared the output of a simple deep learning model (trained with tweeters) with the output of a sentiment dictionary, VADER, targeting Shakespeare’s plays. The results showed that the simple deep learning model led to a similar performance with VADER for Shakespeare’s tragedies and outperformed the sentiment dictionary especially for Shakespeare’s comedies.


sentiment analysis, deep learning, Shakespeare, tweeter data


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서혜진(Seo, Hye-Jin), 대학원생(Graduate Student)동국대학교영어영문학부04620 서울특별시 중구 필동로 1길 30(30 Pildong-ro 1 gil, Jung-gu, Seoul 04620)Tel: 02) 2260-8705E-mail:

이종현(Lee, Jonghyun), 대학원생(Graduate Student)서울대학교(Seoul National University)영어영문학과(Dept. of English Language and Literature)08826 서울특별시 관악구 관악로 1(1 Gwanak-ro, Gwanak-gu, Seoul 08826)Tel: 02) 880-6078E-mail:

신정아(Shin, Jeong-Ah), 교수(Professor)동국대학교(Dongguk University)영어영문학부(Division of English Language and Literature)04620 서울특별시 중구 필동로 1길 30(30 Pildong-ro 1 gil, Jung-gu, Seoul 04620)Tel: 02) 2260-3167E-mail: