{"title":"文章使用率与发表数量之间是否存在格兰杰因果关系?来自 IEEE Xplore 的主题级时间序列证据","authors":"Wencan Tian, Yongzhen Wang, Zhigang Hu, Ruonan Cai, Guangyao Zhang, Xianwen Wang","doi":"10.1007/s11192-024-05038-8","DOIUrl":null,"url":null,"abstract":"<p>In this study, employing the IEEE Xplore database as the data source, articles on different topics (keywords) and their usage data generated from January 2011 to December 2020 were collected and analyzed. The study examined the temporal relationships between these usage data and publication counts at the topic level via Granger causality analysis. The study found that almost 80% of the topics exhibit significant usage-publication interactions from a time-series perspective, with varying time lag lengths depending on the direction of the Granger causality results. Topics that present bidirectional Granger causality show longer time lag lengths than those exhibiting unidirectional causality. Additionally, the study found that the direction of the unidirectional Granger causality was influenced by the significance of a topic. Topics with a greater preference for article usage as the Granger cause of publication counts were deemed more important. The findings’ reliability was confirmed by varying the maximum lag period. This study provides strong support for using usage data to identify hot topics of research.</p>","PeriodicalId":21755,"journal":{"name":"Scientometrics","volume":"12 1","pages":""},"PeriodicalIF":3.5000,"publicationDate":"2024-05-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Does Granger causality exist between article usage and publication counts? A topic-level time-series evidence from IEEE Xplore\",\"authors\":\"Wencan Tian, Yongzhen Wang, Zhigang Hu, Ruonan Cai, Guangyao Zhang, Xianwen Wang\",\"doi\":\"10.1007/s11192-024-05038-8\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>In this study, employing the IEEE Xplore database as the data source, articles on different topics (keywords) and their usage data generated from January 2011 to December 2020 were collected and analyzed. The study examined the temporal relationships between these usage data and publication counts at the topic level via Granger causality analysis. The study found that almost 80% of the topics exhibit significant usage-publication interactions from a time-series perspective, with varying time lag lengths depending on the direction of the Granger causality results. Topics that present bidirectional Granger causality show longer time lag lengths than those exhibiting unidirectional causality. Additionally, the study found that the direction of the unidirectional Granger causality was influenced by the significance of a topic. Topics with a greater preference for article usage as the Granger cause of publication counts were deemed more important. The findings’ reliability was confirmed by varying the maximum lag period. This study provides strong support for using usage data to identify hot topics of research.</p>\",\"PeriodicalId\":21755,\"journal\":{\"name\":\"Scientometrics\",\"volume\":\"12 1\",\"pages\":\"\"},\"PeriodicalIF\":3.5000,\"publicationDate\":\"2024-05-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Scientometrics\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://doi.org/10.1007/s11192-024-05038-8\",\"RegionNum\":3,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Scientometrics","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1007/s11192-024-05038-8","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Does Granger causality exist between article usage and publication counts? A topic-level time-series evidence from IEEE Xplore
In this study, employing the IEEE Xplore database as the data source, articles on different topics (keywords) and their usage data generated from January 2011 to December 2020 were collected and analyzed. The study examined the temporal relationships between these usage data and publication counts at the topic level via Granger causality analysis. The study found that almost 80% of the topics exhibit significant usage-publication interactions from a time-series perspective, with varying time lag lengths depending on the direction of the Granger causality results. Topics that present bidirectional Granger causality show longer time lag lengths than those exhibiting unidirectional causality. Additionally, the study found that the direction of the unidirectional Granger causality was influenced by the significance of a topic. Topics with a greater preference for article usage as the Granger cause of publication counts were deemed more important. The findings’ reliability was confirmed by varying the maximum lag period. This study provides strong support for using usage data to identify hot topics of research.
期刊介绍:
Scientometrics aims at publishing original studies, short communications, preliminary reports, review papers, letters to the editor and book reviews on scientometrics. The topics covered are results of research concerned with the quantitative features and characteristics of science. Emphasis is placed on investigations in which the development and mechanism of science are studied by means of (statistical) mathematical methods.
The Journal also provides the reader with important up-to-date information about international meetings and events in scientometrics and related fields. Appropriate bibliographic compilations are published as a separate section. Due to its fully interdisciplinary character, Scientometrics is indispensable to research workers and research administrators throughout the world. It provides valuable assistance to librarians and documentalists in central scientific agencies, ministries, research institutes and laboratories.
Scientometrics includes the Journal of Research Communication Studies. Consequently its aims and scope cover that of the latter, namely, to bring the results of research investigations together in one place, in such a form that they will be of use not only to the investigators themselves but also to the entrepreneurs and research workers who form the object of these studies.