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Analyzing the success factors of movie box-office using customer reviews with topic analysis
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Jing, Z. | - |
| dc.contributor.author | Park, H.-Y. | - |
| dc.contributor.author | Kim, D.-H. | - |
| dc.contributor.author | Kim, K.-J. | - |
| dc.date.accessioned | 2023-04-28T00:41:08Z | - |
| dc.date.available | 2023-04-28T00:41:08Z | - |
| dc.date.issued | 2020 | - |
| dc.identifier.issn | 0973-5763 | - |
| dc.identifier.uri | https://scholarworks.dongguk.edu/handle/sw.dongguk/7092 | - |
| dc.description.abstract | The film review website has evaluated and rated the film through several movie fan registration member accounts, thus forming a mode of offline viewing and online evaluation. The online commentary of the movie is analyzed by the latent Dirichlet allocation model, and the topics have been obtained by the experiment named as the seven emotions of the viewers. © 2020 Pushpa Publishing House, Prayagraj, India. | - |
| dc.format.extent | 6 | - |
| dc.language | 영어 | - |
| dc.language.iso | ENG | - |
| dc.publisher | Pushpa Publishing House | - |
| dc.title | Analyzing the success factors of movie box-office using customer reviews with topic analysis | - |
| dc.type | Article | - |
| dc.publisher.location | 인도 | - |
| dc.identifier.doi | 10.17654/HMSI120065 | - |
| dc.identifier.scopusid | 2-s2.0-85086019866 | - |
| dc.identifier.bibliographicCitation | JP Journal of Heat and Mass Transfer, v.2020, no.Special Issue 1, pp 65 - 70 | - |
| dc.citation.title | JP Journal of Heat and Mass Transfer | - |
| dc.citation.volume | 2020 | - |
| dc.citation.number | Special Issue 1 | - |
| dc.citation.startPage | 65 | - |
| dc.citation.endPage | 70 | - |
| dc.type.docType | Article | - |
| dc.description.isOpenAccess | N | - |
| dc.description.journalRegisteredClass | scopus | - |
| dc.subject.keywordAuthor | Latent Dirichlet allocation | - |
| dc.subject.keywordAuthor | Movie box-office success | - |
| dc.subject.keywordAuthor | Text mining | - |
| dc.subject.keywordAuthor | topic modeling | - |
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