{"title":"关于“统计学家的共同引用和合作网络”的讨论","authors":"J. Loyal, Yuguo Chen","doi":"10.1080/07350015.2022.2044828","DOIUrl":null,"url":null,"abstract":"We want to congratulate the authors on a fascinating article containing an insightful analysis and their hard work curating the high-quality co-citation and co-authorship networks. These datasets alone are a valuable contribution to the statistics profes-sion, which will undoubtedly inspire future data science projects and advances in methodology. In fact, we are eager to use these networks in our own classrooms and research. Furthermore, the authors use these networks to tackling exciting questions in network science that go beyond the familiar problems of edge imputation and predicting node labels. In doing so, the authors perform a terrific analysis accompanied by exciting new methodology. This analysis serves as a great first step in understanding these networks, and the ideas initiated in this article will certainly stimulate many further research questions. For how do influence the research Or,","PeriodicalId":50247,"journal":{"name":"Journal of Business & Economic Statistics","volume":"40 1","pages":"497 - 498"},"PeriodicalIF":2.9000,"publicationDate":"2022-02-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Discussion of “Co-citation and Co-authorship Networks of Statisticians”\",\"authors\":\"J. Loyal, Yuguo Chen\",\"doi\":\"10.1080/07350015.2022.2044828\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We want to congratulate the authors on a fascinating article containing an insightful analysis and their hard work curating the high-quality co-citation and co-authorship networks. These datasets alone are a valuable contribution to the statistics profes-sion, which will undoubtedly inspire future data science projects and advances in methodology. In fact, we are eager to use these networks in our own classrooms and research. Furthermore, the authors use these networks to tackling exciting questions in network science that go beyond the familiar problems of edge imputation and predicting node labels. In doing so, the authors perform a terrific analysis accompanied by exciting new methodology. This analysis serves as a great first step in understanding these networks, and the ideas initiated in this article will certainly stimulate many further research questions. For how do influence the research Or,\",\"PeriodicalId\":50247,\"journal\":{\"name\":\"Journal of Business & Economic Statistics\",\"volume\":\"40 1\",\"pages\":\"497 - 498\"},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2022-02-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Business & Economic Statistics\",\"FirstCategoryId\":\"100\",\"ListUrlMain\":\"https://doi.org/10.1080/07350015.2022.2044828\",\"RegionNum\":2,\"RegionCategory\":\"数学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Business & Economic Statistics","FirstCategoryId":"100","ListUrlMain":"https://doi.org/10.1080/07350015.2022.2044828","RegionNum":2,"RegionCategory":"数学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
Discussion of “Co-citation and Co-authorship Networks of Statisticians”
We want to congratulate the authors on a fascinating article containing an insightful analysis and their hard work curating the high-quality co-citation and co-authorship networks. These datasets alone are a valuable contribution to the statistics profes-sion, which will undoubtedly inspire future data science projects and advances in methodology. In fact, we are eager to use these networks in our own classrooms and research. Furthermore, the authors use these networks to tackling exciting questions in network science that go beyond the familiar problems of edge imputation and predicting node labels. In doing so, the authors perform a terrific analysis accompanied by exciting new methodology. This analysis serves as a great first step in understanding these networks, and the ideas initiated in this article will certainly stimulate many further research questions. For how do influence the research Or,
期刊介绍:
The Journal of Business and Economic Statistics (JBES) publishes a range of articles, primarily applied statistical analyses of microeconomic, macroeconomic, forecasting, business, and finance related topics. More general papers in statistics, econometrics, computation, simulation, or graphics are also appropriate if they are immediately applicable to the journal''s general topics of interest. Articles published in JBES contain significant results, high-quality methodological content, excellent exposition, and usually include a substantive empirical application.