An Evaluation Method for Content Analysis Based on Twitter Content Influence
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, Euijong | - |
dc.contributor.author | Kim, Young-Gab | - |
dc.contributor.author | Seo, Young-Duk | - |
dc.contributor.author | Seol, Kwangsoo | - |
dc.contributor.author | Baik, Doo-Kwon | - |
dc.date.accessioned | 2021-09-03T05:25:36Z | - |
dc.date.available | 2021-09-03T05:25:36Z | - |
dc.date.created | 2021-06-16 | - |
dc.date.issued | 2017-06 | - |
dc.identifier.issn | 0218-1940 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/83226 | - |
dc.description.abstract | Twitter is a microblogging website, which has different characteristics from any other social networking service (SNS) in that it has one-directional relationships between users with short posts of less than 140 characters. These characteristics make Twitter not only a social network but also a news media. In addition, Twitter posts have been used and analyzed in various fields such as marketing, prediction of presidential elections, and requirement analysis. With an increase in Twitter usage, we need a more effective method to analyze Twitter content. In this paper, we propose a method for content analysis based on the influence of Twitter content. For measuring Twitter influence, we use the number of followers of the content author, retweet count, and currency of time. We perform experiments to compare the proposed method, frequency, numerical statistics, user influence, and sentiment score. The results show that the proposed method is slightly better than the other methods. In addition, we discuss Twitter characteristics and a method for an effective analysis of Twitter content. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | WORLD SCIENTIFIC PUBL CO PTE LTD | - |
dc.title | An Evaluation Method for Content Analysis Based on Twitter Content Influence | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Baik, Doo-Kwon | - |
dc.identifier.doi | 10.1142/S0218194017500310 | - |
dc.identifier.scopusid | 2-s2.0-85021066725 | - |
dc.identifier.wosid | 000404352600007 | - |
dc.identifier.bibliographicCitation | INTERNATIONAL JOURNAL OF SOFTWARE ENGINEERING AND KNOWLEDGE ENGINEERING, v.27, no.5, pp.841 - 867 | - |
dc.relation.isPartOf | INTERNATIONAL JOURNAL OF SOFTWARE ENGINEERING AND KNOWLEDGE ENGINEERING | - |
dc.citation.title | INTERNATIONAL JOURNAL OF SOFTWARE ENGINEERING AND KNOWLEDGE ENGINEERING | - |
dc.citation.volume | 27 | - |
dc.citation.number | 5 | - |
dc.citation.startPage | 841 | - |
dc.citation.endPage | 867 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Artificial Intelligence | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Software Engineering | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.subject.keywordAuthor | - | |
dc.subject.keywordAuthor | content influence | - |
dc.subject.keywordAuthor | retweet | - |
dc.subject.keywordAuthor | follower | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
(02841) 서울특별시 성북구 안암로 14502-3290-1114
COPYRIGHT © 2021 Korea 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.