A Study on Internet Annotation Analysis System Using Opinion Mining
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초록

This paper proposes a big data sentiment analysis method and deep learning implementation method to provide a webtoon comment analysis web page for convenient comment confirmation and feedback of webtoon writers for the development of the cartoon industry in the video animation field. In order to solve the difficulty of automatic analysis due to the nature of Internet comments and provide various sentiment analysis information, long short-term memory (LSTM) algorithm, ranking algorithm, and word2vec algorithm are applied in parallel, and actual popular works are used to verify the validity. If the analysis method of this paper is used, it is easy to expand to other domestic and overseas platforms, and it is expected that it can be used in various video animation content fields, not limited to the webtoon field. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

키워드

AIComment analysisDeep learningLSTM algorithmSentiment analysisVideo animationWebtoon
제목
A Study on Internet Annotation Analysis System Using Opinion Mining
저자
Jeong, Yen-TaeJeon, Byung-Hoon
DOI
10.1007/978-981-99-1252-0_54
발행일
2023-06
유형
Conference paper
저널명
Lecture Notes in Electrical Engineering
1028 LNEE
페이지
409 ~ 413