严尔嘉博士荣获2019年尤金·加菲尔德奖

诸平

Erjia Yan

Associate Professor

Information Science

据科睿唯安（Clarivate Analytics）网站2019年9月4日报道，美国德雷克塞尔大学（Drexel University）计算与信息计量学学院（College of Computing and Informatics，CCI)信息科学系（Department of Information Science）副教授严尔嘉（Dr. Erjia Yan音译）因创新引文分析方法而荣获2019年尤金·加菲尔德奖（2019 Eugene Garfield Award），可以获得奖金2.5万美元。

此消息是2019年9月4日在意大利罗马举行的第17届国际科学计量学与情报计量学会议上，科睿唯安公司（Clarivate Analytics company）的Web of Science Group对外宣布的。该奖项表彰那些致力于创新引文分析方法的科学家，这些方法改善了我们衡量科学研究影响的方式。这个研究领域也被称为科学计量学（scientometrics），是由科学信息研究所（Institute for Scientific Information， ISI）的创始人尤金·加菲尔德博士（Dr Eugene Garfield）开创的。

科学计量学通过帮助政府、资助机构和大学评估他们的工作和投资的影响来塑造科学发现的未来，使他们能够相应地合理分配资金。它还可以为研究人员提供关于他们研究影响的见解以及更广泛的领域。

严博士将利用该奖项研究半结构化或非结构化的文献计量领域（semi-structured or unstructured bibliometric fields），包括标题、摘要和关键词(与传统的单位、期刊协会或作者单位不同)，以理解书目计量指标和数字意义。他的研究将有助于为科学活动的许多方面提供重要的经验基础，例如促进创新;更好和更透明的科学决策;公平发展以及可持续的科学团队。

严博士说:“我一直对引文数据着迷，因为我相信，通过分析数据，我们可以阐明科学是如何开展的，并了解科学家是如何工作的。”

“这个奖项是在一个重要的时刻颁发的，因为在获得德雷克塞尔大学的终身教职后，我有了新的职业目标。我的目标是建立一个研究轮廓，不仅使用引文数据来描述研究领域，而且使用引文支持的推论来帮助利益相关者和委托人做出明智的科学政策决策。有了这个奖项的支持，特别是高质量的科学网数据（Web of Science data），我可以通过设计和开发高影响力的文献计量学研究来推进我的研究，吸引跨学科的观众——这就是我的终生目标。”

严博士除了可以获得25000美元的奖金之外，还可以检索世界上最大的引文索引数据库——Web of Science。严博士还将有机会与1960年由尤金·加菲尔德博士创办的著名的科学信息研究所(Institute for Scientific Information， ISI)合作。ISI专注于发展现有的和新的科学计量方法。

ISI主任乔纳森•亚当斯（Jonathan Adams）教授说:“我们对于严博士当选为2019尤金·加菲尔德引文分析创新奖的获得者深感自豪。严博士的创新方案旨在将“科学学（science of science）”展现到前所未有的程度。我们希望它能帮助研究界深入了解科学知识、创新和影响的生产和传播模式。这一创造性地应用了来自Web of Science的引文数据，是加菲尔德博士在其漫长而杰出的职业生涯中所支持的创新和鼓舞人心的研究类型的完美例证。”

严博士毕业于南京大学（理学学士），后在美国印第安纳大学伯明顿分校（Indiana University Bloomington）获得信息科学硕士学位和博士学位，更多信息请注意浏览相关报道。

Web Of Science Group Announces Recipient Of The 2019 Eugene Garfield Award

ERJIA YAN, PH.D.

I am an assistant professor at Department of Information Science, College of Computing and Informatics (CCI) at Drexel University. My research interests lie in informetrics and scientometrics, scholarly data mining and analysis, and knowledge diffusion studies. My research helps to provide a vital empirical foundation for many facets of scientific activity, such as the propagation of innovations, the promotion of better and more transparent science policymaking, and the development of an equitable and sustainable scientific workforce.

Recent Projects:

Nobel papers citation sentiment change
	This study measures the perception change as reflected in citation sentiment, with the attainment of a Nobel Prize in Chemistry or a Nobel Prize in Physiology or Medicine considered as the status change. The paper identifies 12,393 citances to 25 Nobel papers in PubMed Central and includes a control paper set of 75 papers with 30,851 citances. Results show a moderate increase in citation sentiment toward Nobel papers post-award. Dynamically, for Nobel papers, there is a steady sentiment increase, and a Nobel Prize seems to co-occur with this trend. This trend, however, is not evident in the control paper set. Read more
NIH funding and associated publications
	The conceptual connections between grants and publications are important, yet often overlooked in quantitative studies of science. AThis study aims to offer the first piece of evidence towards this endeavor by analyzing the ratio of keyword matchedness between accepted NIH research grants from 2008 to 2015 and their funded publications. We identified three identified predictors of the outcome: 1) the funding rate of an NIH research program in a specific year, 2) the year difference between grant and publication, and 3) the funding size of a grant. Read more
Open access journal impact
	Closed access journals have a noticeable advantage in social sciences, while open access journals perform well in medical and healthcare domains. After controlling for a journal’s rank and disciplinary differences, there are statistically more closed access journals in the top 10%, Quartile 1, and Quartile 2 categories as measured by CiteScore; in contrast, more open access journals in Quartile 4 gained scientific impact from 2011 to 2015. Considering dynamic and disciplinary trends in tandem, we find that more closed access journals in Social Sciences gained in impact, whereas in Biochemistry and Medicine, more open access journals experienced such gains. Read more
R software mention and citation network analysis
	We developed a software entity extraction method and identified 14,310 instances of R packages across the 13,684 PLoS journal papers mentioning or citing R. A paper-level co-mention network of these packages was visualized and analyzed. We found that the discipline and function of the packages can partly explain the largest clusters. The study offers the first large-scale analysis of R packages’ extensive use in scientific research. As such, it lays the foundation for future explorations of various roles played by software packages in the scientific enterprise. Read more
Research funding vs. citation impact
	Using a regression model with Heckman bias correction, we find that funding has a positive, significant association with a paper’s citations in STEMM fields. Further analyses show that this association is magnified by the factors of multiple authorship and multiple institutions. For funded papers in STEM, multi-author and multiinstitution papers tend to receive even more citations than single-authored and single-institution papers; however, funded papers in Medicine received less gain in citation impact when either factor is considered. Based on the finding that funding support has a stronger association with citation impact when it is treated as a binary variable than as a count variable, this study recommends the allocation of funding to researchers without active funding support, instead of giving awards to those with multiple funding supports at hand. Read more
Data set mentions and citations
	This study provides evidence of data set mentions and citations in multiple disciplines based on a content analysis of 600 publications in PLoS One. We find that data set mentions and citations varied greatly among disciplines in terms of how data sets were collected, referenced, and curated. While a majority of articles provided free access to data, formal ways of data attribution such as DOIs and data citations were used in a limited number of articles. In addition, data reuse took place in less than 30% of the publications that used data, suggesting that researchers are still inclined to create and use their own data sets, rather than reusing previously curated data. This study provides a comprehensive understanding of how data sets are used in science and helps institutions and publishers make useful data policies. Read more
Word semantic change
	We find that for the selected words in PubMed, overall, meanings are becoming more stable in the 2000s than they were in the 1980s and 1990s. At the topic level, the global distance of most topics is declining, suggesting that the words used to discuss these topics are stabilizing semantically. At the word level, this study identifies two different trends in word semantics, as measured by the aforementioned distance metrics: on the one hand, words can form clusters with their semantic neighbors, and these words, as a cluster, coevolve semantically; on the other hand, words can drift apart from their semantic neighbors while nonetheless stabilizing in the global context. In relating our work to language laws on semantic change, we find no overwhelming evidence to support either the law of parallel change or the law of conformity.Read more
Domain-independent term extraction
	This study developed an efficient, domain-independent term extraction method to extract disciplinary vocabularies from a large multidisciplinary corpus of PLoS ONE publications. It finds a power-law pattern in the frequency distributions of terms present in each discipline. The salient relationships amongst these vocabularies become apparent in application of a principal component analysis. For example, Mathematics and Computer and Information Sciences were found to have similar vocabulary use patterns along with Engineering and Physics; while Chemistry and the Social Sciences were found to exhibit contrasting vocabulary use patterns along with the Earth Sciences and Chemistry. Read more
Faculty hiring network analysis
	This study examines academic ranking and inequality in library and information science (LIS) using a faculty hiring network of 643 faculty members from 44 LIS schools in the United States. We study academic inequality using four distinct methods that include downward/upward placement, Lorenz curve, cliques, and egocentric networks of LIS schools and find that academic inequality exists in the LIS community. We show that the percentage of downward placement (68%) is much higher than that of upward placement (22%); meanwhile, 20% of the 30 LIS schools that have doctoral programs produced nearly 60% of all LIS faculty, with a Gini coefficient of 0.53. We also find cliques of highly ranked schools and a core/periphery structure that distinguishes LIS schools of different ranks. Read more
Journal knowledge trading analysis
	This study employs a set of trading based indicators to assess sources’ trading impact. These indicators are applied to several time-sliced source-tosource citation networks that comprise 33,634 sources indexed in the Scopus database. Results show that several interdisciplinary sources, such as Nature, PLOS ONE, Proceedings of the National Academy of Sciences, and Science, and several specialty sources, such as Lancet, Lecture Notes in Computer Science, Journal of the American Chemical Society, Journal of Biological Chemistry, and New England Journal of Medicine, have demonstrated their marked importance in knowledge trading. Furthermore, this study also reveals that, overall, sources have established more trading partners, increased their trading volumes, broadened their trading areas, and diversified their trading contents over the past 15 years from 1997 to 2011. Read more

More research outputs can be found at Research.