@inproceedings{34fc9984bcf24830af2877b929d00f9f,
title = "A Study on Internet Annotation Analysis System Using Opinion Mining",
abstract = "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.",
keywords = "AI, Comment analysis, Deep learning, LSTM algorithm, Sentiment analysis, Video animation, Webtoon",
author = "Jeong, {Yen Tae} and Jeon, {Byung Hoon}",
note = "Publisher Copyright: {\textcopyright} 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.; 14th International Conference on Computer Science and its Applications, CSA 2022 and the 16th KIPS International Conference on Ubiquitous Information Technologies and Applications, CUTE 2022 ; Conference date: 19-12-2022 Through 21-12-2022",
year = "2023",
doi = "10.1007/978-981-99-1252-0_54",
language = "English",
isbn = "9789819912513",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Science and Business Media Deutschland GmbH",
pages = "409--413",
editor = "Park, {Ji Su} and Yang, {Laurence T.} and Yi Pan and Yi Pan and Park, {Jong Hyuk}",
booktitle = "Advances in Computer Science and Ubiquitous Computing - Proceedings of CUTE-CSA 2022",
address = "Germany",
}