R. Onuma, H. Nakayama, H. Kaminaga, Y. Miyadera, Shoichi Nakamura
{"title":"Methods of Analyzing Social Media Articles for Promoting Experience of Doubting Fake","authors":"R. Onuma, H. Nakayama, H. Kaminaga, Y. Miyadera, Shoichi Nakamura","doi":"10.1109/ICOCO53166.2021.9673574","DOIUrl":null,"url":null,"abstract":"Social media is increasingly used as a tool for acquiring and disseminating information. However, there are many fake articles and falsehoods. Accordingly, to make good use of social media, it is important to examine the authenticity of an article, but such examination is often difficult for unskilled people. In this research, we aim to realize a method for to promote experience in identifying fake articles by focusing on the opinion trends of article readers. Here, we describe a framework for this method, including extraction of fake articles and related articles, with a focus on citations.","PeriodicalId":262412,"journal":{"name":"2021 IEEE International Conference on Computing (ICOCO)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE International Conference on Computing (ICOCO)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICOCO53166.2021.9673574","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Social media is increasingly used as a tool for acquiring and disseminating information. However, there are many fake articles and falsehoods. Accordingly, to make good use of social media, it is important to examine the authenticity of an article, but such examination is often difficult for unskilled people. In this research, we aim to realize a method for to promote experience in identifying fake articles by focusing on the opinion trends of article readers. Here, we describe a framework for this method, including extraction of fake articles and related articles, with a focus on citations.