Taerin Yoon, Hyunwoo Han, Hyoji Ha, Juwon Hong, Kyungwon Lee
{"title":"A Conference Paper Exploring System Based on Citing Motivation and Topic","authors":"Taerin Yoon, Hyunwoo Han, Hyoji Ha, Juwon Hong, Kyungwon Lee","doi":"10.1109/PacificVis48177.2020.1010","DOIUrl":null,"url":null,"abstract":"Understanding and maintaining the intended meaning of original text used for citations is essential for unbiased and accurate scholarly work. To this end, this study aims to provide a visual system for exploring the citation relationships and motivations for citations within papers. For this purpose, papers from the IEEE Information Visualization Conference that introduce research on data visualization were collected, and based on the internal citation relationships, citation sentences were extracted and the text were analyzed. In addition, a visualization interface was provided to identify the citation relationships, citation pattern information, and citing motivation. Lastly, the pattern analysis of the citation relationships along with the citing motivation and topic was demonstrated through a case study. Our paper exploring system can confirm the purpose of specific papers being cited by other authors. Furthermore, the findings can help identify the characteristics of related studies based on the target papers.","PeriodicalId":322092,"journal":{"name":"2020 IEEE Pacific Visualization Symposium (PacificVis)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 IEEE Pacific Visualization Symposium (PacificVis)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/PacificVis48177.2020.1010","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
Understanding and maintaining the intended meaning of original text used for citations is essential for unbiased and accurate scholarly work. To this end, this study aims to provide a visual system for exploring the citation relationships and motivations for citations within papers. For this purpose, papers from the IEEE Information Visualization Conference that introduce research on data visualization were collected, and based on the internal citation relationships, citation sentences were extracted and the text were analyzed. In addition, a visualization interface was provided to identify the citation relationships, citation pattern information, and citing motivation. Lastly, the pattern analysis of the citation relationships along with the citing motivation and topic was demonstrated through a case study. Our paper exploring system can confirm the purpose of specific papers being cited by other authors. Furthermore, the findings can help identify the characteristics of related studies based on the target papers.