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1.
《Journal of Informetrics》2023,17(3):101435
How do scientific knowledge and technological knowledge interact to influence patent inventions? This study combines the “Reliance on Science in Patenting” dataset with the PATSTAT database to investigate focal patents and their paper references and patent references. A temporal investigation shows a growing tendency that patents absorb more knowledge from patents than papers. Additionally, we conduct two sets of analyses, namely, studying the knowledge flow among 35 technology fields and 39 science fields and estimating the impact of cited references on patent impact. The results show that the fields are heterogeneous in absorbing scientific knowledge and technological knowledge. The empirical models indicate that the knowledge depth of both science and technology show an inverted U-shaped relationship with patent impact, while the curve of former is steeper. The knowledge breadth of both science and technology present a U-shaped relationship with patent impact, while the curve of latter is steeper. We also explore the impact of time lags and time spread on citations and estimate their joint effects. Our study provides a new understanding of the convergence of scientific knowledge and technological knowledge to facilitate patent inventions. 相似文献
2.
科学-技术关联是指技术创新系统与科学研究系统之间的知识传递关系。探测科学-技术关联的情报学方法是:计量"论文-专利"互引信息,用专利所属的4位IPC类目与论文所属的学科之间的对应关系来反映科学-技术关联。此方法中存在两方面问题:一方面,论文被笼统地视为基础科学的代表,忽略了自然科学体系的"基础科学-技术科学-工程科学"的层级结构;另一方面,IPC类目以"功能"为分类原则且粒度过粗,难以与科学学科合理对应。对科学端的学科层级划分问题和技术端的4位IPC类目细化问题进行研究,对探测科学-技术关联的情报学方法进行改进,并以2006-2009年间的美国催化技术专利和与之具有互引关系的论文为样本进行实验,实验结果反映出更精细的学科-领域对应关系,呈现出更清晰的科学-技术关联图景。 相似文献
3.
[目的/意义] 论文引用专利的“反向引用”也是科学与技术知识关联的重要体现。针对现有“反向引用”研究的不足,分析中国专利技术对世界科学研究的影响。[方法/过程] 搜集整理中国专利被世界科学论文引用的数据,利用文献计量学方法分析“反向引用”的引用频数、技术关联度、引用时滞及技术循环周期等指标,利用社会网络分析方法构建“反向引用”网络,探讨技术领域到科学领域的知识流动情况。[结果/结论] 中国专利技术对世界科学研究的影响力越来越大。科学与技术的双向互动在化学领域体现的最为明显,化学、工程、材料科学三个学科领域较多地吸收了专利知识,技术关联度较高。前1-4年的技术对当前科学影响最大,中国专利被科学文献引用的循环周期较短,平均为4.69年。 相似文献
4.
《Journal of Informetrics》2020,14(4):101074
Demonstrating the practical value of public research has been an important subject in science policy. Here we present a detailed study on the evolution of the citation linkage between life science related patents and biomedical research over a 37-year period. Our analysis relies on a newly-created dataset that systematically links millions of non-patent references to biomedical papers. We find a large disparity in the volume of citations to science among technology sectors, with biotechnology and drug patents dominating it. The linkage has been growing exponentially over a long period of time, doubling every 2.9 years. The U.S. has been the largest producer of cited science for years, receiving nearly half of the citations. More than half of citations goes to universities. We use a new paper-level indicator to quantify to what extent a paper is basic research or clinical medicine. We find that the cited papers are likely to be basic research, yet a significant portion of papers cited in patents that are related to FDA-approved drugs are clinical research. The U.S. National Institute of Health continues to be an important funder of cited science. For the majority of companies, more than half of citations in their patents are authored by public research. Taken together, these results indicate a continuous linkage of public science to private sector inventions. 相似文献
5.
以SJR为数据来源,比较分析了1996-2008年巴西、印度、中国、韩国4个国家发表科技论文数量、可引用文献量、文献被引量、自引量、篇均被引量、去除自引后的篇均被引量、H指数、文献引用率、国际合作量等9个指标。中国发表论文数最多,2003年后每年增加约3万篇。巴西、韩国文献引用率、篇均引用量高,且自引率低;印度居中等水平;中国文献引用率、篇均引用率低且自引率高;国际合作度巴西最高、中国最低。可见中国的科技论文质量与其他3个国家相比,还有一定的差距。 相似文献
6.
Review papers tend to be cited more frequently than regular research articles. This fact, together with the continuous increase of the share of reviews in scientific literature, can have important consequences for the measurement of individuals’ research output, usually based on citation analysis. However, studies evaluating the differences in citations of review papers compared to original research articles are almost non-existing in the literature. This paper presents a thorough analysis of the overcitation and overrepresentation of review papers in the most cited papers of the 35 largest subject categories in Science Citation Index-Expanded. Results indicate the average citations received by reviews depends largely on the research area considered, varying from 1.34 to 6.74 times the citations received by original research articles (average value is 2.95). Correlated with this overcitation, there is an important overrepresentation of reviews in the most cited papers, this overrepresentation being greater when the most highly cited papers are considered, i.e. 0.05% and 0.1% most cited papers, where the share of reviews have increased from 16 to 18% in 1990 to around 40% in 2010. Interestingly, the overcitation and overrepresentation in the most cited papers is more important in the areas with the lowest shares of reviews in total publications. 相似文献
7.
基于F1000与WoS的同行评议与文献计量相关性研究 总被引：1，自引：1，他引：0
为比较同行评议与文献计量方法在科学评价中的有效性及相关性,选取F1000以及Web of Science数据库,采用SPSS16.0软件,将近2000篇论文的F1000因子与Web of Science数据库中指标进行相关性比较。结果显示,F1000因子与统计区间内的被引频次呈显著正相关,同时一些F1000因子很高的论文并没有高频被引,反之亦然。结论指出:从统计学的视角,文献计量指标与同行评议结果具有正向相关性,但是无论是同行评议还是文献计量,单独作为科学评价标准都会有失偏颇,以引文分析为代表的定量指标与同行评议方法的结合将是未来科学评价的主流。 相似文献
8.
《Journal of Informetrics》2023,17(3):101431
In science-technology research, papers and patents are used to represent science and technology, respectively. Detecting sleeping beauty papers and their princes in technology (patent field) could uncover dynamic knowledge contributions from science (paper field) to technology (patent field). However, previous studies have mainly focused on sleeping beauty in science. Some studies have examined SB patents in technology, but SB papers in patents are rarely studied and need to be further discussed. In addition, knowledge could flow along citations. Thus, if one paper is cited by one patent's reference (indirect citation), it also contributes to the patent, even though the patent does not directly cite it. At the same time, indirect citations are rarely discussed in sleeping beauty studies. This could lead to a loss of significant information. Therefore, to reveal the dynamic knowledge contribution from science to technology considering indirect citations, this study proposed a new method of mining sleeping beauty papers in technology and their princes. The lithium-ion battery domain is selected as a case study. The findings are as follows: (1) Most papers do not contribute knowledge to technology continuously, even when considering indirect citations, and the time-varying knowledge contribution strength changes significantly overtime. (2) The knowledge contribution strength with a time delay of more than 11 years occupies 80% of the total knowledge contribution strength. It is suggested that the window period of paper publication evaluation be extended. (3) 22 sleeping beauty papers in technology are detected. Nine papers are among the top 10 regarding the total knowledge contribution strength. (4) The princes of 9 typical sleeping beauty papers in technology are all papers. This implies that the awakening of these papers in technology was all provoked by scientific development. 相似文献
9.
文章旨在再验证专利被引证数作为评估专利价值指标的准确性,并结合专利引文进行深入剖析。利用美国专利数据库检索中置式电动车电控辅助装置、亲水性医用脱脂纱布、军用紧急绷带技术领域的专利,统计专利的被引证数,并采用专家评估结果加以比较。研究结果表明:仅有中置式电动车电控辅助装置专利,专家评估与被引证数指标评估的结果一致;而专利被引证次数因受时间因素影响,早期专利的被引证数较高,但不一定是高价值的专利;存在一些很少被引用,但根据专家评估原则及专利本身具备的特征,被评估为高价值的专利,即可能存在睡美人专利现象。对专利价值评估,不能仅从专利被引证数指标判断,还可应用其他评价方法,更客观反映专利价值,减少专利评价过程中可能存在的风险,以保护企业的技术创新。 相似文献
10.
《Journal of Informetrics》2020,14(3):101039
Predicting the citation counts of academic papers is of considerable significance to scientific evaluation. This study used a four-layer Back Propagation (BP) neural network model to predict the five-year citations of 49,834 papers in the library, information and documentation field indexed by the CSSCI database and published from 2000 to 2013. We extracted six paper features, two journal features, nine author features, eight reference features, and five early citation features to make the prediction. The empirical experiments showed that the performance of the BP neural network is significantly better than those of the six baseline models. In terms of the prediction effect, the accuracy of the model at predicting infrequently cited papers was higher than that for frequently cited ones. We determined that five essential features have significant effects on the prediction performance of the model, i.e., ‘citations in the first two years’, ‘first-cited age’, ‘paper length’, ‘month of publication’, and ‘self-citations of journals’, and the other features contribute only slightly to the prediction. 相似文献
11.
A proposal is made in this paper for a broadening of perspective in evaluative bibliometrics by complementing the (standard) times cited with a cited reference analysis for a field-specific citation impact measurement. The times cited approach counts the citations of a given publication set. In contrast, we change the perspective and start by selecting all papers dealing with a specific research topic or field (the example in this study is research on Aspirin). Then we extract all cited references from the papers of this field-specific publication set and analyse which papers, scientists, and journals have been cited most often. In this study, we use the Chemical Abstracts registry number to select the publications for a specific field. However, the cited reference approach can be used with any other field classification system proposed up to now. 相似文献
12.
《Journal of Informetrics》2014,8(4):904-911
It is well-known that the distribution of citations to articles in a journal is skewed. We ask whether journal rankings based on the impact factor are robust with respect to this fact. We exclude the most cited paper, the top 5 and 10 cited papers for 100 economics journals and recalculate the impact factor. Afterwards we compare the resulting rankings with the original ones from 2012. Our results show that the rankings are relatively robust. This holds both for the 2-year and the 5-year impact factor. 相似文献
13.
《Journal of Informetrics》2019,13(2):485-499
With the growing number of published scientific papers world-wide, the need to evaluation and quality assessment methods for research papers is increasing. Scientific fields such as scientometrics, informetrics, and bibliometrics establish quantified analysis methods and measurements for evaluating scientific papers. In this area, an important problem is to predict the future influence of a published paper. Particularly, early discrimination between influential papers and insignificant papers may find important applications. In this regard, one of the most important metrics is the number of citations to the paper, since this metric is widely utilized in the evaluation of scientific publications and moreover, it serves as the basis for many other metrics such as h-index. In this paper, we propose a novel method for predicting long-term citations of a paper based on the number of its citations in the first few years after publication. In order to train a citation count prediction model, we employed artificial neural network which is a powerful machine learning tool with recently growing applications in many domains including image and text processing. The empirical experiments show that our proposed method outperforms state-of-the-art methods with respect to the prediction accuracy in both yearly and total prediction of the number of citations. 相似文献
14.
The journal impact factor (JIF) is the average of the number of citations of the papers published in a journal, calculated according to a specific formula; it is extensively used for the evaluation of research and researchers. The method assumes that all papers in a journal have the same scientific merit, which is measured by the JIF of the publishing journal. This implies that the number of citations measures scientific merits but the JIF does not evaluate each individual paper by its own number of citations. Therefore, in the comparative evaluation of two papers, the use of the JIF implies a risk of failure, which occurs when a paper in the journal with the lower JIF is compared to another with fewer citations in the journal with the higher JIF. To quantify this risk of failure, this study calculates the failure probabilities, taking advantage of the lognormal distribution of citations. In two journals whose JIFs are ten-fold different, the failure probability is low. However, in most cases when two papers are compared, the JIFs of the journals are not so different. Then, the failure probability can be close to 0.5, which is equivalent to evaluating by coin flipping. 相似文献
15.
利用各种社交网络平台,进行科学论文的获取、分享与传播已成为当前学术交流的重要形式,为此研究社交网络对科技期刊国际传播的影响。利用Elsevier数据库整合的替代计量学指标PlumX,分析PlumX与论文被引频次的关系及其学术特征。基于《中国天然药物》单刊及药理学/毒理学学科分析,均发现高被引论文的PlumX评分显著高于低被引论文,且学科高被引论文的被引频次和PlumX评分呈正相关,此外,高质量的综述和国际论文更易获得社交网络关注。研究结果发现PlumX指标能够对单篇论文的学术影响力进行快速评价,非国际权威期刊中的热点论文也可能获得较高关注,指出英文科技期刊应重视约组社交网络平台发达和应用广泛的相关主流国家优秀稿件,合理利用社交网络平台有助于获得较高的PlumX评分,进而提升发展中国家科学家的话语权。 相似文献
16.
Is more always better? We address this question in the context of bibliometric indices that aim to assess the scientific impact of individual researchers by counting their number of highly cited publications. We propose a simple model in which the number of citations of a publication depends not only on the scientific impact of the publication but also on other ‘random’ factors. Our model indicates that more need not always be better. It turns out that the most influential researchers may have a systematically lower performance, in terms of highly cited publications, than some of their less influential colleagues. The model also suggests an improved way of counting highly cited publications. 相似文献
17.
为评价H指数与影响因子、总被引频次的关系,以2009年《中国期刊引证报告》（扩刊版）中166种医学期刊的H指数、影响因子、总被引频次、引用刊数和来源文献量为源数据,采用SPSSl6．0软件作线性、对数、二次多项式、三次多项式回归拟合和Logistic回归。二维散点图和曲线回归拟合分析均发现,H指数与影响因子、总被引频次、引用刊数呈密切相关,但与来源文献量的相关性不强。因此,H指数、影响因子、总被引频次应相互补充,共同用于医学类期刊学术影响力的评价。 相似文献
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19.
《Journal of Informetrics》2023,17(1):101379
We performed a citation analysis on the Web of Science publications consisting of more than 63 million articles and over a billion citations on 254 subjects from 1981 to 2020. We proposed the Article’s Scientific Prestige (ASP) metric and compared this metric to number of citations (#Cit) and journal grade in measuring the scientific impact of individual articles in the large-scale hierarchical and multi-disciplined citation network. In contrast to #Cit, ASP, that is computed based on the eigenvector centrality, considers both direct and indirect citations, and provides steady-state evaluation cross different disciplines. We found that ASP and #Cit are not aligned for most articles, with a growing mismatch amongst the less cited articles. While both metrics are reliable for evaluating the prestige of articles such as Nobel Prize winning articles, ASP tends to provide more persuasive rankings than #Cit when the articles are not highly cited. The journal grade, that is eventually determined by a few highly cited articles, is unable to properly reflect the scientific impact of individual articles. The number of references and coauthors are less relevant to scientific impact, but subjects do make a difference. 相似文献
20.
This study investigates the trend of global concentration in scientific research and technological innovation around the world. It accepts papers and patents as appropriate data for revealing the development and status of science and technology respectively. The performance of these outputs in production and citation impact is taken into consideration in the analysis. The findings suggest that both papers and patents are geographically concentrated on a small number of countries, including the United States, the United Kingdom, Japan, Germany, and France. China has made great progress in paper production and citation impact, and Taiwan and Korea have experienced a rapid growth in patents over the past years. The degree of concentration dramatically decreases when the data from the United States are excluded, indicating the effects of the U.S.’s participation on the concentration. Patents show a higher degree of concentration than papers. With time-varying aspects taken into consideration, the study indicates that the degree of concentration of papers and patents has gradually decreased over time. The concentration of patents has declined more slowly than that of papers. This decrease of the concentration is mainly due to the reduction of the predominant role of the U.S. in world R&D output. 相似文献