Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 백승익 | - |
dc.date.accessioned | 2021-11-01T02:07:50Z | - |
dc.date.available | 2021-11-01T02:07:50Z | - |
dc.date.issued | 2020-04 | - |
dc.identifier.citation | International Journal of Advanced Science and Technology, v. 29, no. 4, page. 291-303 | en_US |
dc.identifier.issn | 2005-4238 | - |
dc.identifier.issn | 2207-6360 | - |
dc.identifier.uri | http://sersc.org/journals/index.php/IJAST/article/view/6307 | - |
dc.identifier.uri | https://repository.hanyang.ac.kr/handle/20.500.11754/166077 | - |
dc.description.abstract | Background/Objectives: The purpose of this study is to empirically investigate the semantic similarity of documents posted on different forms of media about specific social issues. Methods/Statistical analysis: Online text data were collected from personal blogs and Internet news published on a major Korean portal site, NAVER. To collect text data from online media, the study used R programming language for web crawling. We examined what effects medium characteristics had on the content of conveyed messages by using a keyword extraction method based on TF-IDF, which is a text mining method, and the cosine similarity measurement method. Findings: The results of this study demonstrate that there were differences in the major keywords extracted from messages conveyed by the three forms of media, but the similarity between keyword-to-keyword matrices extracted from the media was confirmed by a Mantel test, and there were statistically significant degrees of similarity among these matrices. We were therefore able to discover similarities of message content conveyed by each medium. Improvements/Applications: For this study, we used only blog and news data published on a single Korean portal site. The text data better be collected from variety of channels in future studies. | en_US |
dc.description.sponsorship | This work was supported by the research fund of Hanyang University (HY-2018). | en_US |
dc.language.iso | en | en_US |
dc.publisher | Science and Engineering Research Support Society | en_US |
dc.subject | Media characteristic | en_US |
dc.subject | Online media | en_US |
dc.subject | Offline media | en_US |
dc.subject | Text mining | en_US |
dc.subject | TF-IDF | en_US |
dc.subject | Similarity analysis | en_US |
dc.title | Exploring impacts of media characteristics on message content using text mining | en_US |
dc.type | Article | en_US |
dc.relation.no | 4 Special Issue | - |
dc.relation.volume | 29 | - |
dc.relation.page | 291-303 | - |
dc.relation.journal | International Journal of Advanced Science and Technology | - |
dc.contributor.googleauthor | Baek, Seung Ik | - |
dc.contributor.googleauthor | Park, Seungri | - |
dc.contributor.googleauthor | Kim, Jinhwa | - |
dc.relation.code | 2020010280 | - |
dc.sector.campus | S | - |
dc.sector.daehak | SCHOOL OF BUSINESS[S] | - |
dc.sector.department | SCHOOL OF BUSINESS ADMINISTRATION | - |
dc.identifier.pid | sbaek | - |
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