Malgorzata J. Krawczyk, Mateusz Libirt, Krzysztof Malarz
{"title":"科学论文隶属关系中的排名分布:不同形式的齐夫定律有和没有高阶逆参与比","authors":"Malgorzata J. Krawczyk, Mateusz Libirt, Krzysztof Malarz","doi":"10.1016/j.joi.2025.101684","DOIUrl":null,"url":null,"abstract":"<div><div>Although often difficult to define and parameterize, scientific collaboration between scientists from different centers and different countries or continents seems to be an interesting and important issue in an increasingly interconnected world. One natural source of such information is scientific papers that include the affiliations of the authors. They do not allow determining the origin of the authors (at least currently), but they can be used to show how large the participation of individual countries in the scientific world is. By analyzing a large set of publications, it is possible to collect chains covering countries and their multiplicity in the affiliations of the authors, and on this basis it is possible to show the most common patterns of collaborating scientific teams. Since in this article we are interested in a more general, statistical approach, the obtained chains are used to calculate an indicator (known as the inverse participation ratio) that expresses different patterns of the distribution of participation of individual countries. We show that the scientific world is another example of universal laws observed in the world because the obtained distribution of inverse participation ratio values obeys Zipf's law.</div></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"19 3","pages":"Article 101684"},"PeriodicalIF":3.4000,"publicationDate":"2025-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Rank-based distributions in scientific papers affiliations: Different forms of Zipf's law with and without higher order inverse participation ratios\",\"authors\":\"Malgorzata J. Krawczyk, Mateusz Libirt, Krzysztof Malarz\",\"doi\":\"10.1016/j.joi.2025.101684\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Although often difficult to define and parameterize, scientific collaboration between scientists from different centers and different countries or continents seems to be an interesting and important issue in an increasingly interconnected world. One natural source of such information is scientific papers that include the affiliations of the authors. They do not allow determining the origin of the authors (at least currently), but they can be used to show how large the participation of individual countries in the scientific world is. By analyzing a large set of publications, it is possible to collect chains covering countries and their multiplicity in the affiliations of the authors, and on this basis it is possible to show the most common patterns of collaborating scientific teams. Since in this article we are interested in a more general, statistical approach, the obtained chains are used to calculate an indicator (known as the inverse participation ratio) that expresses different patterns of the distribution of participation of individual countries. We show that the scientific world is another example of universal laws observed in the world because the obtained distribution of inverse participation ratio values obeys Zipf's law.</div></div>\",\"PeriodicalId\":48662,\"journal\":{\"name\":\"Journal of Informetrics\",\"volume\":\"19 3\",\"pages\":\"Article 101684\"},\"PeriodicalIF\":3.4000,\"publicationDate\":\"2025-05-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Informetrics\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1751157725000483\",\"RegionNum\":2,\"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":"Journal of Informetrics","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1751157725000483","RegionNum":2,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
Rank-based distributions in scientific papers affiliations: Different forms of Zipf's law with and without higher order inverse participation ratios
Although often difficult to define and parameterize, scientific collaboration between scientists from different centers and different countries or continents seems to be an interesting and important issue in an increasingly interconnected world. One natural source of such information is scientific papers that include the affiliations of the authors. They do not allow determining the origin of the authors (at least currently), but they can be used to show how large the participation of individual countries in the scientific world is. By analyzing a large set of publications, it is possible to collect chains covering countries and their multiplicity in the affiliations of the authors, and on this basis it is possible to show the most common patterns of collaborating scientific teams. Since in this article we are interested in a more general, statistical approach, the obtained chains are used to calculate an indicator (known as the inverse participation ratio) that expresses different patterns of the distribution of participation of individual countries. We show that the scientific world is another example of universal laws observed in the world because the obtained distribution of inverse participation ratio values obeys Zipf's law.
期刊介绍:
Journal of Informetrics (JOI) publishes rigorous high-quality research on quantitative aspects of information science. The main focus of the journal is on topics in bibliometrics, scientometrics, webometrics, patentometrics, altmetrics and research evaluation. Contributions studying informetric problems using methods from other quantitative fields, such as mathematics, statistics, computer science, economics and econometrics, and network science, are especially encouraged. JOI publishes both theoretical and empirical work. In general, case studies, for instance a bibliometric analysis focusing on a specific research field or a specific country, are not considered suitable for publication in JOI, unless they contain innovative methodological elements.