Cited 0 time in
A Study on Internet Annotation Analysis System Using Opinion Mining
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Jeong, Yen-Tae | - |
| dc.contributor.author | Jeon, Byung-Hoon | - |
| dc.date.accessioned | 2024-08-08T07:01:34Z | - |
| dc.date.available | 2024-08-08T07:01:34Z | - |
| dc.date.issued | 2023-06 | - |
| dc.identifier.issn | 1876-1100 | - |
| dc.identifier.issn | 1876-1119 | - |
| dc.identifier.uri | https://scholarworks.dongguk.edu/handle/sw.dongguk/19383 | - |
| dc.description.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. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. | - |
| dc.format.extent | 5 | - |
| dc.language | 영어 | - |
| dc.language.iso | ENG | - |
| dc.publisher | Springer Science and Business Media Deutschland GmbH | - |
| dc.title | A Study on Internet Annotation Analysis System Using Opinion Mining | - |
| dc.type | Article | - |
| dc.publisher.location | 독일 | - |
| dc.identifier.doi | 10.1007/978-981-99-1252-0_54 | - |
| dc.identifier.scopusid | 2-s2.0-85163992639 | - |
| dc.identifier.bibliographicCitation | Lecture Notes in Electrical Engineering, v.1028 LNEE, pp 409 - 413 | - |
| dc.citation.title | Lecture Notes in Electrical Engineering | - |
| dc.citation.volume | 1028 LNEE | - |
| dc.citation.startPage | 409 | - |
| dc.citation.endPage | 413 | - |
| dc.type.docType | Conference paper | - |
| dc.description.isOpenAccess | N | - |
| dc.description.journalRegisteredClass | scopus | - |
| dc.subject.keywordAuthor | AI | - |
| dc.subject.keywordAuthor | Comment analysis | - |
| dc.subject.keywordAuthor | Deep learning | - |
| dc.subject.keywordAuthor | LSTM algorithm | - |
| dc.subject.keywordAuthor | Sentiment analysis | - |
| dc.subject.keywordAuthor | Video animation | - |
| dc.subject.keywordAuthor | Webtoon | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
30, Pildong-ro 1-gil, Jung-gu, Seoul, 04620, Republic of Korea+82-2-2260-3114
Copyright(c) 2023 DONGGUK UNIVERSITY. ALL RIGHTS RESERVED.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.
