{"title":"Comparing patent in-text and front-page references to science","authors":"Jian Wang , Suzan Verberne","doi":"10.1016/j.joi.2024.101564","DOIUrl":null,"url":null,"abstract":"<div><p>Patent references to science provide a paper trail of knowledge flow from science to innovation, and have attracted a lot of attention in recent years. However, we understand little about the differences between two types of patents references: front-page vs. in-text. While both types of references are becoming more accessible, we still lack a systematic understanding on how results are sensitive to which type of references are being analyzed in science and innovation studies. Using a dataset of 33,337 USPTO biotech utility patents, their 860,879 in-text and 637,570 front-page references to Web of Science journal articles, we found a remarkable low overlap between these two types of references. We also found that in-text references are more basic and have more scientific citations than front-page references. The difference in interdisciplinarity and novelty is small when comparing at the reference level and insignificant when comparing at the patent level. We analyze the association between patent value (as measured by patent citations and market value) and characteristics of referenced sciences. Results are substantially different between in-text and front-page references. In addition, in-text referenced papers have a higher chance of being listed on the front-page of the same patent when they are moderately basic, less interdisciplinary, less novel, and have more scientific citations.</p></div>","PeriodicalId":48662,"journal":{"name":"Journal of Informetrics","volume":"18 4","pages":"Article 101564"},"PeriodicalIF":3.4000,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1751157724000774/pdfft?md5=0f53abc32da83b95eefc022668120f82&pid=1-s2.0-S1751157724000774-main.pdf","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Informetrics","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1751157724000774","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}
引用次数: 0
Abstract
Patent references to science provide a paper trail of knowledge flow from science to innovation, and have attracted a lot of attention in recent years. However, we understand little about the differences between two types of patents references: front-page vs. in-text. While both types of references are becoming more accessible, we still lack a systematic understanding on how results are sensitive to which type of references are being analyzed in science and innovation studies. Using a dataset of 33,337 USPTO biotech utility patents, their 860,879 in-text and 637,570 front-page references to Web of Science journal articles, we found a remarkable low overlap between these two types of references. We also found that in-text references are more basic and have more scientific citations than front-page references. The difference in interdisciplinarity and novelty is small when comparing at the reference level and insignificant when comparing at the patent level. We analyze the association between patent value (as measured by patent citations and market value) and characteristics of referenced sciences. Results are substantially different between in-text and front-page references. In addition, in-text referenced papers have a higher chance of being listed on the front-page of the same patent when they are moderately basic, less interdisciplinary, less novel, and have more scientific citations.
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.