No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
How do Price medalists’ scholarly impact change before and after their awards?
Abstract
How a scholar's achievement and productivity may change by the award of an academic prize is a topic of a long-term interest in research fields such as scientometrics. Numerous studies have explored the impact of receiving a Nobel Prize, a Turing Award, and other international awards on laureates' scholarly performance, but relatively less attention has been paid to the impact of Derek John de Solla Price Medal on its recipients. This paper adopts the methodology of Structural Variation Analysis (SVA) to evaluate how Price medalists' research are impacted, if any, in terms of citation, h-index, and structural variation patterns in underlying collaborative networks. Moreover, we compare the SVA metrics with other indicators such as composite scores and Highly Cited Researchers (HCR). Our results show that: a Price Medal award may not necessarily boost the medalist’s scholarly potential, actual academic impact and collaboration patterns in a degree that is statistically significant. But the SVA method is a better indicator to evaluate the Price Medalist, especially in five-year time windows.
... The complete sample of 70 researchers is similar to other studies on academic elites (e.g., Derek John de Solla Price Medal: 29; Turing Award: 72) (Hou et al., 2021;Jin et al., 2021). Most of the sCSE work in the fields of agricultural and biological sciences, followed by arts and humanities, and medicine, whereas the CSE work mostly in arts and humanities, and medicine, followed by agricultural and biological sciences, and biochemistry, genetics and molecular biology (Fig. 2). ...
... The before/after pushing effect of receiving the special mention analysed here consisted only in an exploratory observation considering the discussion focused on the top-three most prolific researchers per category. Further studies on impact/citation effects after receiving an award could use more robust methodologies, such as regression discontinuity or structural variation analysis (Hou et al., 2021). ...
The research agenda on global academic elites (e.g., those awarded the Nobel Prize) has overlooked academic awards and elites from developing countries and the public symbolic recognition of scientific elites by research awards. In this study, we examine the bibliometric features of individual researcher profiles of those participants who received a special mention in Colombia's most prestigious prize in the sciences: the Alejandro Ángel Escobar Prize (AAEP). First, we chart the citation per article trend of Colombia's most prolific researchers before and after receiving the special mention and the AAEP. We then compare the special mention group with those awarded the AAEP, using a composite citation indicator of six scientific impact and productivity indices to estimate (1) bulk impact (number of citations and h index) and (2) authorship order adjusted impact (Schreiber hm index; total citations for articles of which the scientist is the single author; total citations for articles of which the scientist is the single or first author; and total citations for articles of which the scientist is the single, first, or last author). Results show that there is no overall halo effect in citation per article after receiving the special mention or the AAEP. Such recognition comes after an academically productive career marked by multiple citations per article peaks. There is no clear-cut division between the composite citation indicator of those awarded a special mention and those awarded the AAEP. Findings place the profile of local authors in an adjusted and inclusive framework that takes full cognisance of the scientific elites in developing countries.
... The complete sample of 70 researchers is similar to other studies on academic elites (e.g., Derek John de Solla Price Medal: 29; Turing Award: 72) (Hou et al., 2021;Jin et al., 2021). Most of the sCSE work in the fields of agricultural and biological sciences, followed by arts and humanities, and medicine, whereas the CSE work mostly in arts and humanities, and medicine, followed by agricultural and biological sciences, and biochemistry, genetics and molecular biology (Fig. 2). ...
... The before/after pushing effect of receiving the special mention analysed here consisted only in an exploratory observation considering the discussion focused on the top-three most prolific researchers per category. Further studies on impact/citation effects after receiving an award could use more robust methodologies, such as regression discontinuity or structural variation analysis (Hou et al., 2021). ...
The research agenda on global academic elites (e.g., those awarded the Nobel Prize) has overlooked academic awards and elites from developing countries together with those who participate in such competitions, fail to win an award, but receive a special mention instead. In this study, we examine the bibliometric features of individual researcher profiles of those participants who received a special mention in Colombia's most prestigious prize in the sciences: the Alejandro Ángel Escobar Prize (AAEP). First, we chart the citation/paper trend of Colombia's most prolific authors before and after receiving the special mention. We then compare the special mention group with those awarded the AAEP, using the composite indicator (C) of six scientific impact and productivity indices to estimate (1) bulk impact (number of citations and h index) and (2) authorship order adjusted impact (Schreiber hm index; total citations for papers of which the scientist is the single author; total citations for papers of which the scientist is the single or first author; and total citations for papers of which the scientist is the single, first, or last author). According to the authors' output profile, the most multidisciplinary AAEP category was physical and natural sciences, the least: social sciences and humanities. Results show that there is no overall halo effect in citation/paper after receiving the special mention. Such recognition comes after an academically productive career marked by multiple citation/paper peaks. There is no clear-cut division between the C of those awarded a special mention and those awarded the AAEP. Findings place the profile of local authors in an adjusted and inclusive framework that takes full cognisance of the scientific elites in developing countries.
... The Price award is the most prestigious international accolade in the field of scientometrics, honoring scholars who have made outstanding contributions to scientometrics or informetrics (Hou et al., 2021). Their research is of high caliber and represents the field prominently (Grácio et al., 2023). ...
Identifying key knowledge foundation is a significant branch of citation analysis. The identification of key knowledge foundations and visualization of their knowledge dissemination maps are pivotal in understanding the development and dynamics of scientific fields. While the referenced publication year spectroscopy (RPYS) analysis method can elucidate the historical roots and significant papers within a knowledge domain, it cannot effectively depict the thematic content of these historical works. Consequently, this study employs the field of scientometrics as a case study to propose a novel approach that integrates RPYS and topic clustering techniques for the identification and analysis of key knowledge foundations. Utilizing publication data and references from recipients of the prestigious Price Award in the field of scientometrics as representative samples, we identified 303 key references along with 5832 unduplicated citation records, encompassing a total of 2109 unduplicated papers. Subsequently, we employed topic clustering to construct a topic citation network comprising 40 distinct topics. This study offers a comprehensive analysis of key knowledge foundations in scientometrics through an overall analysis, temporal stage analysis, and scholar-specific analysis of the topic citation network. Our findings illuminate classic topics that have significantly contributed to the development of scientometrics, the evolution of key knowledge foundations over time, and the unique impacts of individual scholars. This study underscores the interconnectedness of research themes while highlighting the enduring influence of foundational research. This approach not only establishes a robust framework for identifying and analyzing key knowledge foundations in scientometrics but also serves as a valuable reference for identifying and evaluating key knowledge foundations across other research fields.
... (2) Moreover, our preceding research (Hou et al., 2020;Hou, Zheng, Zhang, & Chen, 2021) provides pieces of evidence that ΔM has wide applicability to measure significant papers and authors. ...
Previous studies diverged on whether boundary-spanning papers are cited more heavily, however , there is as yet no research that explains how boundary-spanning papers affect citation counts from a causal view and how they influence knowledge diffusion in citation network. To this end, we utilized Propensity Score Matching to clarify the relationship between the citation counts and the degree of boundary-spanning of 281,707 papers in the field of Astronomy (AS), Natural Language Processing (NLP), Library and Information Science (LIS) based on causal inference. We also adopted Sentence-BERT to compute the content similarity among seed papers, cited papers, citing papers, to imply how seed paper affects citation network when knowledge diffuses. According to the similarity between seed paper and citing paper, cited paper and citing paper, we defined paper's role in citation network as four types: Disseminator, Broker, Trigger, and Outlier. The major findings are as follows: (1) Papers with a higher degree of boundary-spanning are more likely to be cited heavily; (2) Disseminator and Outlier account for a larger proportion in three disciplines, while Broker and Trigger account for a smaller proportion; (3) The degree of boundary-spanning and citation counts of four types vary in three disciplines. This work, which reveals paper's value and role in citation network from the perspective of content, has implications to provide some enlightenment for the paper's evaluation.
... We assigned him to the EnvSci category since he was awarded twice in that category. The CSE sample contains a similar sample of researchers compared to previous studies on non-Nobel laureates (e.g., 29 recipients of the Derek John de Solla Prize Medal [72]). Table 2 presents the bibliometric descriptives. ...
A well-established agenda on the research output, impact, and structure of global scientific elites such as Nobel Prize laureates has generated interest in the scientific elites from developing countries. However, this topic has not been investigated in detail. This study, first, deploys science mapping techniques to provide a comprehensive analysis of the output, impact, and structure of the Colombian scientific elite, i.e., researchers awarded with the Alejandro Ángel Escobar Foundation National Prize 1990–2020, known locally as the Colombian Nobel. Second, we conducted a productivity and impact comparison between the Colombian scientific elite and Nobel Prize laureates in science and economics by means of a stratified random sample 1990–2020 via the composite citation indicator proposed by Ioannidis et al. Findings showed that the Colombian scientific elite has a broader agenda than indexing titles in internationally renowned bibliographic databases. The Colombian scientific elite also showed positive growth, which is an inverse trend compared with the sample of Nobel laureate productivity. There were no noticeable changes in productivity/impact before and after receiving the Alejandro Ángel Escobar Foundation National Prize. Institutional collaboration within the Colombian scientific elite displayed the highest betweenness (brokerage) role of world/local top-tier universities. However, only two Colombian scientific elite members published an article with two Nobel Prize laureates. Most of the research profiles reflected the national output priorities, but were found to diverge from the national focus in respect of strategic research capacities. The interleaving of the Colombian scientific elite and Nobel Prize laureates—particularly between the 3rd and 2nd quartiles—enabled a more nuanced analysis of the local impact in the global scientific landscape. Our findings also contrast with previous findings on the lower research impact of authors from Latin America, despite their involvement as contributors to reputable journals, and also shed light on the research performance-impact standards and agenda between the global North and South and provide an in-context assessment of outstanding local research.
... In the analysis of structural variation, the modularity change rate, the change of intercluster connection, and the change of centrality distribution all could be used to measure the academic influence. Strikingly, ∆M is used in the analysis of CiteSpace by Professor Chen Chaomei, who developed the software and explained the calculation method in detail [33]. In this paper, ∆M was also chosen why the higher the value of ∆M was, the greater the potential influence of the new publication on the current network was. ...
Background:
The new media provides a convenient platform to access, use and exchange health information. And as a special group of health care, maternal health care is still of international concern due to their high mortality rate. Scientific research is a good way to provide advice on how to improve maternal health through stringent reasoning and accurate data. However, the dramatic increase of publications, the diversity of themes, and the dispersion of researchers may reduce the quality of information and increase the difficulty of selection. Thus, this study aims to analyze the research progress on maternal health under the global new media environment, exploring the current research hotspots and frontiers.
Methods:
A scientometric analysis was carried out by CiteSpace5.7.R1. In total, 2270 articles have been further analyzed to explore top countries and institutions, potential articles, research frontiers, and hotspots.
Results:
The publications ascended markedly, from 29 in 2008 to 472 publications by 2020. But there is still a lot of room to grow, and the growth rate does not conform to the Price's Law. Research centers concentrated in Latin America, such as the University of Toronto and the University of California. The work of Larsson M, Lagan BM and Tiedje L had high potential influence. Most of the research subjects were maternal and newborn babies, and the research frontiers were distributed in health education and psychological problems. Maternal mental health, nutrition, weight, production technology, and equipment were seemingly hotspots.
Conclusion:
The new media has almost brought a new era for maternal health, mainly characterized by psychological qualities, healthy and reasonable physical conditions and advanced technology.
... We assigned him to the EnvSci category since he was awarded twice in that category. The CSE sample contains a similar sample of researchers compared to previous studies on non-Nobel laureates (e.g., 29 recipients of the Derek John de Solla Prize Medal [72]). Table 2 presents the bibliometric descriptives. ...
A well established agenda on the research output, impact, and structure of global scientific elites such as Nobel Prize laureates has generated interest in the scientific elites from developing countries. This study deploys science mapping techniques to provide a comprehensive analysis of the output, impact, and structure of the Colombian scientific elite, i.e., researchers awarded with the Alejandro Angel Escobar Foundation National Prize 1990 2020, known locally as the Colombian Nobel. Findings showed that the Colombian scientific elite has a broader agenda than indexing titles in internationally renowned bibliographic databases. The Colombian scientific elite also showed positive growth, which is an inverse trend compared with Nobel laureate productivity. There were no noticeable changes in productivity and impact before and after receiving the prize. Institutional collaboration within the Colombian scientific elite displayed the highest betweenness (brokerage) role of world and local top-tier universities. However, only two Colombian scientific elite members published an article with two Nobel Prize laureates. Most of the research profiles reflected the national output priorities, but were found to diverge from the national focus in respect of strategic research capacities. This study also conducted a productivity and impact comparison with Nobel Prize laureates in science and economics by means of a stratified random sample 1990-2020 via the composite indicator proposed by Ioannidis et al. The interleaving of the Colombian scientific elite and Nobel Prize laureates, particularly between the 3rd and 2nd quartiles, enabled a more nuanced analysis of the local impact in the global scientific landscape.
In this paper, we investigate the properties of the science-wide author databases’ standardised citation indicators produced since 2015 by a team of researchers led by John P. A. Ioannidis. Based on data from Scopus, the researchers published close to 200,000 of the most-cited authors across all scientific fields and ranked them using a composite indicator that includes six citation metrics (total citations; Hirsch h-index; coauthorship-adjusted Schreiber hm-index; the number of citations to papers as a single author; the number of citations to papers as a single or first author; and the number of citations to papers as a single, first, or last author). We look at the quality of these new rankings to suggest improvements. Specifically, we try to correct for correlation among variables and the deviation between the purported weights of the variables, as declared by the developers, and the effective weights based on the theory of global sensitivity analysis. We aim to ascertain if our modified measure is an improvement over the existing one by addressing the issue of redundant data due to correlated variables. Lacking a ground truth based on a ‘true’ ranking possibly supported by independent data, we content ourselves for the purpose of the present analysis with benchmarking against a best practice. Given that most practitioners have reservations against linear aggregation approaches (Munda, Social multi-criteria evaluation for a sustainable economy, Springer, Berlin, 2008; Balinski & Laraki, Majority judgment: Measuring, ranking, and electing, Mass, 2011; Arrow, Social choice and individual values, Martino Fine Books, Eastford, 2012 [1951]), while those based on the method of Condorcet are considered by many as a good practice (Munda, Social multi-criteria evaluation for a sustainable economy, Springer, Berlin, 2008; Roy, Multicriteria methodology for decision aiding, Springer, Cham, 1996), we entrust of defence of our modified ranking on a pairwise comparison between linear aggregation and Condorcet.
Nobel laureates offer a range of expertise to researchers interested in generating scientific productivity by capitalizing on their ability to collaborate with other outstanding researchers. However, current knowledge on whether and how a scholar’s research areas can be leveraged for scientific productivity has not been examined empirically. There has been scant conceptualization of the underlying processes responsible for utilizing research areas, and the results have been equivocal. We propose and test the intermediate mechanisms of number of collaborations and collaboration diversity as two distinctive capabilities that may explain how a research area drives a scientist’s productivity. Our conceptual model posits that the link between research areas and scientific productivity is neither simple nor direct. An empirical test on Nobel laureates demonstrates the complexity of innovation generation. Two pathways from research areas to scientific productivity are revealed: number of collaborations and collaboration diversity both mediate the link, but the role of research areas is negatively moderated by the scholar’s dependence on external knowledge to their academic collaboration. Our theory is thereby confirmed. Finally, expected findings and contributions are also discussed.
The Matthew effect is widely used by researchers across disciplines. However, few studies have focused on this effect’s magnitude variation on the background of the open access movement and expanded avenues to obtain information. Citation is the most widespread and basic form of scholarly recognition in the reward system of science, therefore, scientists are motivated to refer to the work of their peers where reference is due. This study assumes that the Matthew effect may not play a major role in science anymore and uses citations as a proxy to measure this effect, and calculates the citation fluctuation of Noble Laureates’ key publications before and after winning the award during 1901–2016. The results show that the coefficient of variation of citations is smaller for publications published after 1980 than for those published before. The median of citations in chemistry is higher than that for in physics, physiology, or medicine. Additionally, over 90% of publications published after 1980 were recognized by their community pre-award, while the ratio consisted of 84% and 75% for 1940–1980 and 1900–1940, respectively. Furthermore, the time range between publication and year awarded plays a role in this phenomenon. The study suggests a potential magnitude decrease in the Matthew effect, which is a reminder that most researchers nowadays will recognize the importance of scientific breakthrough in its early stage.
We propose a method to measure the potential scholarly impact of researchers based on network structural variations they introduced to the underlying author co-citation network of their field. We applied the method to the information science field based on 91,978 papers published between 1979 and 2018 from the Web of Science. We divided the entire period into eight consecutive intervals and measured structural variation change rates (ΔM) of individual authors in corresponding author co-citation networks. Four types of researchers are identified in terms of temporal dynamics of their potential scholarly impact—1) Increasing, 2) Decreasing, 3) Sustained, and 4) Transient. The study contributes to the understanding of how researchers’ scholarly impact might evolve in a broad context of the corresponding research community. Specifically, this study illustrated a crucial role played by structural variation metrics in measuring and explaining the potential scholarly impact of a researcher. This method based on the structural variation analysis offers a theoretical framework and a practical platform to analyze the potential scholarly impact of researchers and their specific contributions.
Scientific ideas seldom come entirely from nothing; they often originate from existing knowledge. In this study, we aim to identify the relationship between the knowledge recency and Nobel Prize-winning articles (NPs) from the perspectives of gender, career stage, and country of the orig-inators. Scientific literatures published by Nobel laureates in the Physiology or Medicine field are treated as NPs, and the age of references cited in those literatures are considered a measurement of knowledge recency. Results show that most NPs in this field have been focused on literature with a low mean and median recency, and over half of these works have cited equal to or more than 68 % of recent literature published within five years. Contrary to traditional wisdom, the greatest discoveries made after 1980 have shown an increasing favor to older literature. We also find that there has been no gender gap for the recency of NPs; however, career stage has been an important factor influencing knowledge recency, which means older researchers tend to cite more earlier articles than others.
Throughout history, a relatively small number of individuals have made a profound and lasting impact on science and society. Despite long-standing, multi-disciplinary interests in understanding careers of elite scientists, there have been limited attempts for a quantitative, career-level analysis. Here, we leverage a comprehensive dataset we assembled, allowing us to trace the entire career histories of nearly all Nobel laureates in physics, chemistry, and physiology or medicine over the past century. We find that, although Nobel laureates were energetic producers from the outset, producing works that garner unusually high impact, their careers before winning the prize follow relatively similar patterns to those of ordinary scientists, being characterized by hot streaks and increasing reliance on collaborations. We also uncovered notable variations along their careers, often associated with the Nobel Prize, including shifting coauthorship structure in the prize-winning work, and a significant but temporary dip in the impact of work they produce after winning the Nobel Prize. Together, these results document quantitative patterns governing the careers of scientific elites, offering an empirical basis for a deeper understanding of the hallmarks of exceptional careers in science.
The h-index has attracted wide attention from both scientometricians and science policy makers since it was proposed in 2005. Advocates champion h-index for its simplicity embracing both quantity and quality, while also express concern about its abuse in research evaluation practices and database-dependence attribute. We argue that it is increasingly important to calculate and interpret the h-index precisely along with the rapid evolution of bibliographic databases. In memory of Dr. Judit Bar-Ilan, we join the h-index discussion in Scientometrics by further probing a similar “which h-index” question via comparing different versions of h-index within the Web of Science. In this article we put forward the reasons of different WoS h-indices from two perspectives, which are often neglected by bibliometric studies. We suggest that users should specify the details of data sources of h-index calculation for research promotion and evaluation practices.
The achievements of all 97 Nobel laureates in Chemistry, Economy, Medicine, and Physics of the period 2010–2019 are compared with achievements of top non-Nobel scientists in terms of standard bibliometric indicators (number of publications, number of citations, Hirsch index), of the numbers of highly cited papers and of hot papers (as defined by WoS®), and of c, a composite score (Ioannidis et al. in PLoS Biol 14:e1002501, 2016). Ninety recent Nobel laureates were in top 100,000 scientists in terms of c, and 45 recent Nobel laureates were in top 6000 scientists in terms of c. Only 32 recent Nobel laureates were in top 6000 scientists in terms of ch (Hirsch-type index with self-citations excluded),
32 recent Nobel laureates were in top 6000 scientists in terms of the number of citations (self-citations excluded), 17 recent Nobel laureates were among the 6000 Highly Cited Researchers (WoS®), 4 recent Nobel laureates were in top 6000 scientists in terms of the number of hot papers, and 2 recent Nobel laureates were in top 6000 scientists in terms of the number of highly cited papers.
Advisor–advisee relationships in academic genealogy offer opportunities to understand the contribution of a mentor in shaping the research community. In this paper, we adapt the bibliometric g-index to study the mentorship role of a researcher. We call the new index -index. It has some important differences from the mentorship h-index or the -index. We compute the values of the and indices for researchers indexed in the Mathematics Genealogy Project and the Academic Family Tree. We observe for the majority of researchers, these index values are zero, but in non-zero cases, sometimes, the -index can be significantly higher than the -index. Moreover, the -index decays less rapidly to zero than the -index. It appears the -index can be used to discriminate between researchers with the same -index. We study how these mentorship indices are correlated with other indicators of academic success, and how they are correlated across generations of researchers.
Although more than a million academic papers have been posted on Facebook, there is little detailed research about which fields or cross-field issues are involved and whether there are field or public interest relationships between Facebook mentions and future citations. In response, we identified health and biomedical scientific papers mentioned on Facebook and assigned subjects to them using the MeSH and Science Metrix journal classification schema. Multistage adaptive LASSO and unpenalized least-squares regressions were used to model Facebook mentions by fields and MeSH terms. The fields Science and Technology, General and Internal Medicine, Complementary and Alternative Medicine, and Sport Sciences produced higher Facebook mention counts than average. However, no MeSH cross-field issue differences were found in the rate of attracting Facebook mentions. The relationship between Facebook mentions and citations varies between both fields and MeSH cross-field issues. General and Internal Medicine, Cardiovascular System and Hematology and Developmental Biology have the strongest correlations between Facebook mentions and citations, probably due to high citation rates and high Facebook visibility in these areas.
Can alternative metrics (altmetrics) data be used to measure societal impact? We wrote this literature overview of empirical studies in order to find an answer to this question. The overview includes two parts. The first part, “societal impact measurements”, explains possible methods and problems in measuring the societal impact of research, case studies for societal impact measurement, societal impact considerations at funding organizations, and the societal problems that should be solved by science. The second part of the review, “altmetrics”, addresses a major question in research evaluation, which is whether altmetrics are proper indicators for measuring the societal impact of research. In the second part we explain the data sources used for altmetrics studies and the importance of field-normalized indicators for impact measurements. This review indicates that it should be relevant for impact measurements to be oriented towards pressing societal problems. Case studies in which societal impact of certain pieces of research is explained seem to provide a legitimate method for measuring societal impact. In the use of altmetrics, field-specific differences should be considered by applying field normalization (in cross-field comparisons). Altmetrics data such as social media counts might mainly reflect the public interest and discussion of scholarly works rather than their societal impact. Altmetrics (Twitter data) might be especially fruitfully employed for research evaluation purposes, if they are used in the context of network approaches. Conclusions based on altmetrics data in research evaluation should be drawn with caution.
The year of 2017 for the 50th anniversary of the Turing Award, which represents the top-level award in the computer science field, is a milestone. We study the long-term evolution of the Turing Award Collaboration Network, and it can be considered as a microcosm of the computer science field from 1974 to 2016. First, scholars tend to publish articles by themselves at the early stages, and they began to focus on tight collaboration since the late 1980s. Second, compared with the same scale random network, although the Turing Award Collaboration Network has small-world properties, it is not a scale-free network. The reason may be that the number of collaborators per scholar is limited. It is impossible for scholars to connect to others freely (preferential attachment) as the scale-free network. Third, to measure how far a scholar is from the Turing Award, we propose a metric called the Turing Number (TN) and find that the TN decreases gradually over time. Meanwhile, we discover the phenomenon that scholars prefer to gather into groups to do research with the development of computer science. This article presents a new way to explore the evolution of academic collaboration network in the field of computer science by building and analyzing the Turing Award Collaboration Network for decades.
The effective evaluation of the impact of a scholarly article is a significant endeavor; for this reason, it has garnered attention. From the perspective of knowledge flow, this paper extracted various knowledge flow patterns concealed in articles citation counts to describe the citation impact of the articles. First, the intensity characteristic of knowledge flow was investigated to distinguish the different citation vitality of articles. Second, the knowledge diffusion capacity was examined to differentiate the size of the scope of articles’ influences on the academic environment. Finally, the knowledge transfer capacity was discussed to investigate the support degree of articles on the follow-up research. Experimental results show that articles got more citations recently have a higher knowledge flow intensity. The articles have various impacts on the academic environment and have different supporting effects on the follow-up research, representing the differences in their knowledge diffusion and knowledge transfer capabilities. Compared with the single quantitative index of citation frequency, these knowledge flow patterns can carefully explore the citation value of articles. By integrating the three knowledge flow patterns to examine the total citation impact of articles, we found that the articles exhibit distinct value of citation impact even if they were published in the same field, in the same year, and with similar citation frequencies.
Citation metrics are widely used and misused. We have created a publicly available database of 100,000 top scientists that provides standardized information on citations, h-index, coauthorship-adjusted hm-index, citations to papers in different authorship positions, and a composite indicator. Separate data are shown for career-long and single-year impact. Metrics with and without self-citations and ratio of citations to citing papers are given. Scientists are classified into 22 scientific fields and 176 subfields. Field- and subfield-specific percentiles are also provided for all scientists who have published at least five papers. Career-long data are updated to end of 2017 and to end of 2018 for comparison.
Altmetrics have been proposed as a way to assess the societal impact of research. Although altmetrics are already in use as impact or attention metrics in different contexts, it is still not clear whether they really capture or reflect societal impact. This study is based on altmetrics, citation counts, research output and case study data from the UK Research Excellence Framework (REF), and peers' REF assessments of research output and societal impact. We investigated the convergent validity of altmetrics by using two REF datasets: publications submitted as research output (PRO) to the REF and publications referenced in case studies (PCS). Case studies, which are intended to demonstrate societal impact, should cite the most relevant research papers. We used the MHq' indicator for assessing impact - an indicator which has been introduced for count data with many zeros. The results of the first part of the analysis show that news media as well as mentions on Facebook, in blogs, in Wikipedia, and in policy-related documents have higher MHq' values for PCS than for PRO. Thus, the altmetric indicators seem to have convergent validity for these data. In the second part of the analysis, altmetrics have been correlated with REF reviewers' average scores on PCS. The negative or close to zero correlations question the convergent validity of altmetrics in that context. We suggest that they may capture a different aspect of societal impact (which can be called unknown attention) to that seen by reviewers (who are interested in the causal link between research and action in society).
Alternative metrics (aka altmetrics) are gaining increasing interest in the scientometrics community as they can capture both the volume and quality of attention that a research work receives online. Nevertheless, there is limited knowledge about their effectiveness as a mean for measuring the impact of research if compared to traditional citation-based indicators. This work aims at rigorously investigating if any correlation exists among indicators, either traditional (i.e. citation count and h-index) or alternative (i.e. altmetrics) and which of them may be effective for evaluating scholars. The study is based on the analysis of real data coming from the National Scientific Qualification procedure held in Italy by committees of peers on behalf of the Italian Ministry of Education, Universities and Research.
This research aims to investigate the effect of the Derek de Solla Price memorial award reception on publishing behavior of medalists through comparing their research performance in 5 years before and after the prize. The current study was conducted using scientometric indicators. The population of the study was comprised of all scholarly output of 26 Price medalists. Web of Science and Journal Citation Reports were utilized for data collection. Results of the study revealed that the research performance of medalists in all five studied indicators, namely the number of publications, the number of citations received, the quality of journals in which their articles have been published, the number of research collaborations and the number of research collaborators, improved after prize reception, but not in a statistically significant level. Moreover, the tendency of prize winners to international research collaboration has increased in a notable manner upon prize reception. We can conclude that he reception of Price medal in scientometrics has no statistically significant effect on the medalists’ scientific publication, citation impact and research collaboration patterns.
To explore the relation between early career performance or recognition and receiving the Nobel Prize in Economic Sciences, we compare winners of the John Bates Clark Medal, the most prestigious early career recognition for economists, with other successful scholars. The initial comparison combines JBCM winners with scholars published in leading economics journals, controlling for educational background (institution conferring the Ph.D.) and publication and citation success. We then narrow the comparison group down to those given relatively early recognition (based on age category) in the form of other major awards. Lastly, we compare the JBCM awardees with synthetic counterfactuals that best resemble their pre-award academic career performance. All three analyses provide strong support for the notion that winning the JBCM is related to receiving the Nobel Prize, the award of which is also correlated with early career performance success as measured by number of publications and citations.
Recently, two new indicators (Equalized Mean-based Normalized Proportion Cited, EMNPC; Mean-based Normalized Proportion Cited, MNPC) were proposed which are intended for sparse scientometrics data. The indicators compare the proportion of mentioned papers (e.g. on Facebook) of a unit (e.g., a researcher or institution) with the proportion of mentioned papers in the corresponding fields and publication years (the expected values). In this study, we propose a third indicator (Mantel-Haenszel quotient, MHq) belonging to the same indicator family. The MHq is based on the MH analysis - an established method in statistics for the comparison of proportions. We test (using citations and assessments by peers, i.e. F1000Prime recommendations) if the three indicators can distinguish between different quality levels as defined on the basis of the assessments by peers. Thus, we test their convergent validity. We find that the indicator MHq is able to distinguish between the quality levels in most cases while MNPC and EMNPC are not. Since the MHq is approved in this study as a valid indicator, we apply the indicator to six zero-inflated altmetrics data and test whether different altmetrics sources are related to quality. The results for the various altmetrics demonstrate that the relationship between altmetrics (Wikipedia, Facebook, blogs, and news data) and assessments by peers is not given as strong as the relationship between citations and assessments by peers. Actually, the relationship between citations and peer assessments is about two to three times stronger than the association between altmetrics and assessments by peers.
Academic genealogy can be defined as the study of intellectual heritage that is undertaken through the relationship between a professor (advisor/mentor) and student (advisee) and on the basis of these ties, it establishes a social framework that is generally represented by an academic genealogy graph. Obtaining relevant knowledge of academic genealogy graphs makes it possible to analyse the academic training of scientific communities, and discover ancestors or forbears who had special skills and talents. The use of metrics for characterizing this kind of graph is an active form of knowledge extraction. In this paper, we set out a formal definition of a metric called ‘genealogical index’, which can be used to assess how far researchers have affected advisor–advisee relationships. This metric is based on the bibliometrics h-index and its definition can be broadened to measure the effect of researchers on several generations of scientists. A case study is employed that includes an academic genealogy graph consisting of more than 190,000 Ph.D.s registered in the Mathematics Genealogy Project. Additionally, we compare the genealogical indices obtained from both the Fields Medal and Wolf Prize winners, and found that the latter has had a greater impact than the former.
Skills underlying scientific innovation and discovery generally develop within an academic community, often beginning with a graduate mentor’s laboratory. In this paper, a network analysis of doctoral student-dissertation advisor relationships in The Academic Family Tree indicates the pattern of Nobel laureate mentoring relationships is non-random. Nobel laureates had a greater number of Nobel laureate ancestors, descendants, mentees/grandmentees, and local academic family, supporting the notion that assortative processes occur in the selection of mentors and mentees. Subnetworks composed entirely of Nobel laureates extended across as many as four generations. Several successful mentoring communities in high-level science were identified, as measured by number of Nobel laureates within the community. These communities centered on Cambridge University in the latter nineteenth century and Columbia University in the early twentieth century. The current practice of building web-based academic networks, extended to include a wider variety of measures of academic success, would allow for the identification of modern successful scientific communities and should be promoted.
Electronic supplementary material
The online version of this article (doi:10.1007/s11192-017-2364-4) contains supplementary material, which is available to authorized users.
The purpose of this editorial note was to conduct a citation analysis of the Webology journal in order to show the journal impact factor, h-index, i10-index, i20-index, and patent citations. This note indicates to what extent the Webology journal is used and cited by the international scientific community. The results show that the total number of citations to Webology papers on Google Scholar was 2423 and the total number of citations received by i20 papers (i.e., 24 papers with at least 20 citations) was 1693. This reveals that i20 papers received 70 percent of all citations to Webology.
Social media has become integrated into the fabric of the scholarly communication system in fundamental ways: principally through scholarly use of social media platforms and the promotion of new indicators on the basis of interactions with these platforms. Research and scholarship in this area has accelerated since the coining and subsequent advocacy for altmetrics -- that is, research indicators based on social media activity. This review provides an extensive account of the state-of-the art in both scholarly use of social media and altmetrics. The review consists of two main parts: the first examines the use of social media in academia, examining the various functions these platforms have in the scholarly communication process and the factors that affect this use. The second part reviews empirical studies of altmetrics, discussing the various interpretations of altmetrics, data collection and methodological limitations, and differences according to platform. The review ends with a critical discussion of the implications of this transformation in the scholarly communication system.
Many fields face an increasing prevalence of multi-authorship, and this poses challenges in assessing citation metrics. Here, we explore multiple citation indicators that address total impact (number of citations, Hirsch H index [H]), co-authorship adjustment (Schreiber Hm index [Hm]), and author order (total citations to papers as single; single or first; or single, first, or last author). We demonstrate the correlation patterns between these indicators across 84,116 scientists (those among the top 30,000 for impact in a single year [2013] in at least one of these indicators) and separately across 12 scientific fields. Correlation patterns vary across these 12 fields. In physics, total citations are highly negatively correlated with indicators of co-authorship adjustment and of author order, while in other sciences the negative correlation is seen only for total citation impact and citations to papers as single author. We propose a composite score that sums standardized values of these six log-transformed indicators. Of the 1,000 top-ranked scientists with the composite score, only 322 are in the top 1,000 based on total citations. Many Nobel laureates and other extremely influential scientists rank among the top-1,000 with the composite indicator, but would rank much lower based on total citations. Conversely, many of the top 1,000 authors on total citations have had no single/first/last-authored cited paper. More Nobel laureates of 2011-2015 are among the top authors when authors are ranked by the composite score than by total citations, H index, or Hm index; 40/47 of these laureates are among the top 30,000 by at least one of the six indicators. We also explore the sensitivity of indicators to self-citation and alphabetic ordering of authors in papers across different scientific fields. Multiple indicators and their composite may give a more comprehensive picture of impact, although no citation indicator, single or composite, can be expected to select all the best scientists.
Along the history, many researchers provided remarkable contributions to science, not only advancing knowledge but also in terms of mentoring new scientists. Currently, identifying and studying the formation of researchers over the years is a challenging task as current repositories of theses and dissertations are cataloged in a decentralized way through many local digital libraries. In this paper, we give a first step towards building a large repository that records the academic genealogy of researchers across fields and countries. We crawled data from the Networked Digital Library of Theses and Dissertations (NDLTD) and develop a framework to extract academic genealogy trees from this data and provide a series of analyses that describe the main properties of the academic genealogy trees. Our effort identified interesting findings related to the structure of academic formation, which highlight the importance of cataloging academic genealogy trees. We hope our initial framework will be the basis of a much larger crowdsourcing system.
We investigate whether Nobel laureates’ collaborative activities undergo a negative change following prize reception by using publication records of 198 Nobel laureates and analyzing their coauthorship patterns before and after the Nobel Prize. The results overall indicate less collaboration with new coauthors post award than pre award. Nobel laureates are more loyal to collaborations that started before the Prize: looking at coauthorship drop-out rates, we find that these differ significantly between coauthorships that started before the Prize and coauthorships after the Prize. We also find that the greater the intensity of pre-award cooperation and the longer the period of pre-award collaboration, the higher the probability of staying in the coauthor network after the award, implying a higher loyalty to the Nobel laureate.
e-Research is changing practices and dynamics in social research by the incorporation of advanced e-tools to process data and increase scientific collaboration. Previous research shows a positive attitude of investigators through e-Re search and shows a fast incorporation of e-Tools, in despite of many cultural resistances to the change. This paper examines the current state (attitudes, tools and practices) of e-Research in the field of Media and Communication Studies in Latin America, Spain and Portugal. A total of 316 researchers of the region answered an online survey during the last 2 months of 2011. Findings confirm an optimistic attitude through e-Research and an often use of e-Tools to do research. Even though, most of them informed to use basic e-Tools (e. g. e-mail, commercial videoconference, office software and social networks) instead of advanced technologies to process huge amount of data (e. g. Grid, simulation software and Internet2) or the incorporation to Virtual Research Communities. Some of the researchers said that they had an "intensive" (31%) and "often" (53%) use of e-Tools, but only 22% stated that their computer capacity was not enough to manage and process data. The paper evidences the gap between e-Research in Communications and e-Research in other disciplines; and makes recommendations for its implementation.
Increasingly, academics have to demonstrate that their research has academic impact. Universities normally use journal rankings and journal impact factors to assess the research impact of individual academics. More recently, citation counts for individual articles and the h-index have also been used to measure the academic impact of academics. There are, however, several serious problems with relying on journal rankings, journal impact factors and citation counts. For example, articles without any impact may be published in highly ranked journals or journals with high impact factor, whereas articles with high impact could be published in lower ranked journals or journals with low impact factor. Citation counts can also be easily gamed and manipulated and the h-index disadvantages early career academics. This paper discusses these and several other problems and suggests alternatives such as post-publication peer review and open-access journals.
Today, it is not clear how the impact of research on other areas of society than science should be measured. While peer review and bibliometrics have become standard methods for measuring the impact of research in science, there is not yet an accepted framework within which to measure societal impact. Alternative metrics (called altmetrics to distinguish them from bibliometrics) are considered an interesting option for assessing the societal impact of research, as they offer new ways to measure (public) engagement with research output. Altmetrics is a term to describe web-based metrics for the impact of publications and other scholarly material by using data from social media platforms (e.g. Twitter or Mendeley). This overview of studies explores the potential of altmetrics for measuring societal impact. It deals with the definition and classification of altmetrics. Furthermore, their benefits and disadvantages for measuring impact are discussed.
Alternative metrics are currently one of the most popular research topics in
scientometric research. This paper provides an overview of research into three
of the most important altmetrics: microblogging (Twitter), online reference
managers (Mendeley and CiteULike) and blogging. The literature is discussed in
relation to the possible use of altmetrics in research evaluation. Since the
research was particularly interested in the correlation between altmetrics
counts and citation counts, this overview focuses particularly on this
correlation. For each altmetric, a meta-analysis is calculated for its
correlation with traditional citation counts. As the results of the
meta-analyses show, the correlation with traditional citations for
micro-blogging counts is negligible (pooled r=0.003), for blog counts it is
small (pooled r=0.12) and for bookmark counts from online reference managers,
medium to large (CiteULike pooled r=0.23; Mendeley pooled r=0.51). Since the
added value of an alternative metric, as an additional metric compared with
traditional citation counts, is greater the less it correlates with traditional
citation counts, the greatest added value - according to the meta-analysis - is
associated with Twitter citations.
Can altmetric data be validly used for the measurement of societal impact?
The current study seeks to answer this question with a comprehensive dataset
(about 100,000 records) from very disparate sources (F1000, Altmetric, and an
in-house database based on Web of Science). In the F1000 peer review system,
experts attach particular tags to scientific papers which indicate whether a
paper could be of interest for science or rather for other segments of society.
The results show that papers with the tag "good for teaching" do achieve higher
altmetric counts than papers without this tag - if the quality of the papers is
controlled. At the same time, a higher citation count is shown especially by
papers with a tag that is specifically scientifically oriented ("new finding").
The findings indicate that papers tailored for a readership outside the area of
research should lead to societal impact. If altmetric data is to be used for
the measurement of societal impact, the question arises of its normalization.
In bibliometrics, citations are normalized for the papers' subject area and
publication year. This study has taken a second analytic step involving a
possible normalization of altmetric data. As the results show there are
particular scientific topics which are of especial interest for a wide
audience. Since these more or less interesting topics are not completely
reflected in Thomson Reuters' journal sets, a normalization of altmetric data
should not be based on the level of subject categories, but on the level of
topics.
Some findings are reported from the three-year Researchers of Tomorrow study of research behaviour among doctoral students in 'Generation Y'. Commissioned by the British Library and UK Joint Information Systems Committee, it is the most intensive study of its kind to date. Generation Y doctoral students are sophisticated information-seekers and users of complex information sources, highly competent in but not dazzled by technology and acutely aware of authority and authenticity issues in research. The study indicates heavy dependence on secondary, published resources as the basis for original research, which may have implications for research quality and the 'research apprenticeship' experience. eJournals dominate across all subject disciplines; authentication of access to and licensing limitations on subscription-based resources are a source of frustration. There is widespread lack of understanding about open access. Generation Y doctoral students are not keen users of new technology applications in their research and prefer those that do not challenge existing research work practices. The majority work alone, not in research teams, sharing research outputs only with peers. Despite potential benefits of greater openness and sharing they are constrained by lack of confidence in their research work and the need for them to demonstrate originality in research findings.
Based on the foundation laid by the h-index we introduce and study the R- and AR-indices. These new indices eliminate some of the disadvantages of the h-index, especially when they are used in combination with the h-index. The R-index measures the h-core’s citation intensity, while AR goes one step further and takes the age of publications into account. This allows for an index that can actually increase and decrease over time. We propose the pair (h, AR) as a meaningful indicator for research evaluation. We further prove a relation characterizing the h-index in the power law model.
The purpose of this study is to identify the universities and research scholars who have had the greatest impact on the field of management during the past quarter century and the factors that influence their impact. Using bibliometric techniques, the authors examined 30 management journals to identify the 100 most-cited universities and 150 most-cited authors from 1981 to 2004. The analysis included more than 1,600 universities and 25,000 management scholars across five individual time periods. The findings showed that (a) a relatively small proportion of universities and scholars accounted for the majority of the citations in the field; (b) total publications accounted for the majority of the variance in university citations; (c) university size, the number of PhDs awarded, research expenditures, and endowment assets had the biggest impact on university publications; and (d) total publications, years in the field, graduate school reputation, and editorial board memberships had the biggest effect on a scholar's citations.
We propose a two-dimensional bibliometric index that strikes a balance between quantity (as measured by the number of publications of a researcher) and quality (as measured by the number of citations to those publications). While the square of h-index is determined by the maximum area square that fits under the citation curve of an author when plotting the number of citations in decreasing order, the rec-index is determined by the maximum area rectangle that fits under the curve. In this context we may distinguish between authors with a few very highly-cited publications, who may have carried out some influential research, and prolific authors, who may have many publications but fewer citations per publication. The influence of a researcher may be measured via a restricted version of the rec-index, the -index, which is the maximum area vertical rectangle that fits under the citation curve. Similarly, the prolificity of a researcher may be measured via the -index, which is the maximum area horizontal rectangle that fits under the citation curve. This leads to the proposal of the two-dimensional bibliometric index , which captures both aspects of a researcher’s output. We present a comprehensive empirical analysis of this two-dimensional index on two datasets: a large set of Google Scholar profiles (representing “typical” researchers) and a small set of Nobel prize winners. Our results demonstrate the potential of this two-dimensional index, since for both data sets there is a statistically significant number of researchers for whom is greater than . In particular, for nearly 25% of the Google Scholar researchers and for nearly 60% of the Nobel prize winners, is greater than .
Objective:
A diverse array of measures are used to evaluate academic physicians. One critical factor is the scholarly influence an author has on the research discourse within a field. The National Institutes of Health recently developed the Relative Citation Ratio (RCR) as a method to quantify the influence of published research. The aim of this study was to examine the academic influence of vascular surgeons using RCR within common vascular disease research fields.
Methods:
Using the PubMed and National Institutes of Health iCite databases, scientific fields of abdominal and thoracic aortic aneurysm, peripheral artery disease (PAD), cerebral vascular occlusive disease, deep venous thrombosis (DVT), and venous insufficiency were queried for the highest rated RCR articles in each category (2007-2012). To calculate the RCR, article citation rates are divided by an expected citation rate derived from performance of articles in the same field, with the resulting RCR being level and field independent. Article categories were divided into basic science, health services, and clinical research on the basis of two independent reviews. For articles, academic backgrounds of the first, second, and last authors ("influential authors") were collected analyzing procedural specialty: surgery, medicine subspecialty (cardiology, neurology, nephrology), radiology/engineering, and other (anesthesia and pediatrics). Statistical significance between scientific fields and academic background was determined using Student t-test or analysis of variance followed by Newman-Keuls post hoc test.
Results:
The academic influence of vascular surgeons varied substantially by the scientific field. Vascular surgeons compared with medical specialists were found to have the highest academic influence in abdominal aortic aneurysm research, composing 51% of the influential authors on the highest rated RCR studies (5.9 ± 0.8 vs 5.6 ± 0.8; P = .6). In contrast, vascular surgeons composed only 13% of influential authors compared with medical specialists in DVT (RCR, 2.6 ± 0.3 vs 15.7 ± 1.7; P < .003) and 18% in PAD (RCR, 1.9 ± 0.5 vs 2.1 ± 0.2; P = .78) research fields. Grouping all vascular fields of study together, no difference in RCR was found between vascular surgery and radiology/engineering. However, the mean RCR was significantly lower for vascular surgeons compared with medical subspecialties (4.5 ± 0.4 vs 6.8 ± 0.5; P < .05).
Conclusions:
Vascular surgeons exhibit a moderate academic influence in the field of aneurysmal disease but lag behind medical subspecialists in high-impact scientific contributions to the fields of PAD and DVT. Innovative strategies and collaborations are likely needed to increase the influence of vascular surgeons on the academic discourse of several vascular disease research fields.
Abstract
OBJECTIVE:
The purpose of this study is to define the publication patterns and the impact of self-citation among program directors of surgical fellowships.
METHODS:
Program directors were identified through the respective fellowship accrediting council and association websites for eleven surgical subspecialties. Using the Scopus database, the number of publications, citations, self-citations, and h-indices were calculated.
RESULTS:
781 program directors were identified. The mean number ± SD of publications, citations, and h-index for the cohort were 74.6 ± 88.2, 2141 ± 3486, and 18.8 ± 14.5, respectively. The self-citation rate for the entire cohort was 3.17%. After excluding self-citations, the h-index remained unchanged for 72% of surgeons. After propensity score matching for h-index, colorectal surgeons (1.48%, p = 0.04) had significantly lower self-citation rates.
CONCLUSION:
Overall, self-citation is infrequent among program directors of surgical fellowships. There is a lower rate of self-citation among colorectal surgeons when compared to program directors in other specialties with similar baseline metrics.
Data show that apart from their prize-winning work, the careers of Nobel laureates follow the same patterns as those of the majority of scientists.
To find a more effective method for evaluating the achievements of individual scholars, this study proposes a Dh-index analysis method from experts’ perspective under the guidance of concept of Academic Credit Evaluation. This method inherits the advantages of traditional h-index and analyses the information valued by experts for the purpose of finding high impact scholars with a lower cost. Using Dh-index analysis method to calculate Dh-index and Dg-index, the study identified a list about scholars’ academic status under the perspective of experts. Indices used in the method were listed in descending order by researching citations between 2000 and 2016 in Scientometrics and Journal of Informetrics during the process. In order to support the conclusions obtained from this method and test the feasibility and effectiveness of this method, we use Derek John de Solla Price Medal (DJSP Medal) as an example. The method simulates the selection process of DJSP Medal and the result is highly in accordance with the actual DJSP Medal winners, which proves that the method mentioned in this article is valid and might be used to predict potential winners. Citation behaviours can reflect some endogenous customs in academic communication, and can be used as effective signals to evaluate the status of scholars in their field. Hence, based on domain experts’ citation behaviours, Dh-index analysis method can effectively combine qualitative and quantitative evaluation techniques. With less manpower, lower cost, simpler manipulation, more robustness and other advantages, the method can not only acquire valuable reference information, but also predict potential winners of DJSP Medal and other academic awards.
Scientific contributions take many forms, not all of which result in fame or are captured in traditional metrics of success (e.g., h factor). My focus is on one of the most lasting and important contributions a scientist can make: training scientists who go on to train scientists, who in turn train more scientists, etc. Academic genealogies provide many examples of scientists whose names might not be recognizable today but who trained psychologists that went on to publish very influential work. Of course success results from a combination of many factors (including but not limited to the student’s abilities and motivation, luck, institutional resources, mentoring, etc.), but the field should find more ways to acknowledge the role that mentoring does play.
Professional decisions about hiring, tenure, promotion, funding, and honors are informed by assessments of scholarly impact. As a measure of influence, citations are produced by experts but accessible to nonexperts. The h index is the largest number h such that an individual has published at least h works cited at least h times apiece. This is easy to understand and calculate, as or more reliable and valid than alternative citation measures, and highly robust to missing or messy data. Striving for a large h index requires both productivity and influence, which provides healthy incentives for researchers striving for eminence through scientific impact. A number of factors that can influence h are discussed to promote the mindful use of what might otherwise be an ambiguous or misleading measure. The h index adds a transparent, objective component to assessments of scholarly impact, and even academic eminence, that merits at least two cheers.
Mentoring has proven again and again to be an effective workforce development tool. A 2009 study by Triple Creek looked at the impact of e-mentoring (specifically "open mentoring") on productivity and effectiveness. Eighty-eight percent of open mentoring users agreed that their productivity increased due to mentoring, and 97 percent of users who spent at least one hour per month on mentoring were satisfied with their experience. Participants rated "expanding my network," "interpersonal effectiveness," and "confidence in role" as the top three areas in which they improved the most as a result of mentoring.
Despite much in-depth investigation of factors influencing the coauthorship evolution in various scientific fields, our knowledge about how efficiency or creativity is linked to the longevity of collaborative relationships remains very limited. We explore what Nobel laureates’ coauthorship patterns reveal about the nature of scientific collaborations looking at the intensity and success of scientific collaborations across fields and across laureates’ collaborative lifecycles in physics, chemistry, and physiology/medicine. We find that more collaboration with the same researcher is actually no better for advancing creativity: publications produced early in a sequence of repeated collaborations with a given coauthor tend to be published better and cited more than papers that come later in the collaboration with the same coauthor. Our results indicate that scientific collaboration involves conceptual complementarities that may erode over a sequence of repeated interactions.
Knowledge generation is key to economic growth, and scientific prizes are designed to encourage it. But how does winning a prestigious prize affect future output? We compare the productivity of Fields Medal recipients (winners of the top mathematics prize) to that of similarly brilliant contenders. The two groups have similar publication rates until the award year, after which the winners' productivity declines. The medalists begin to "play the field," studying unfamiliar topics at the expense of writing papers. It appears that tournaments can have large postprize effects on the effort allocation of knowledge producers. © 2015 by the Board of Regents of the University of Wisconsin System.
Visualization of scientific results using networks has become popular in scientometric research. We provide base maps for Mendeley reader count data using the publication year 2012 from the Web of Science data. Example networks are shown and explained. The reader can use our base maps to visualize other results with the VOSViewer. The proposed overlay maps are able to show the impact of publications in terms of readership data. The advantage of using our base maps is that it is not necessary for the user to produce a network based on all data (e.g., from 1 year), but can collect the Mendeley data for a single institution (or journals, topics) and can match them with our already produced information. Generation of such large-scale networks is still a demanding task despite the available computer power and digital data availability. Therefore, it is very useful to have base maps and create the network with the overlay technique.
International academic awards are popular as incentives and rewards for academics all over the world, and have played a significant role in the performance evaluations of individuals and institutions. However, little is known about the relative importance of awards and the relationships between awards. This study aims to establish a comprehensive global map of important international academic awards, which visually presents the relative reputations of awards and the close or distant relationships between awards. By surveying the reputations of the preselected 207 awards, 90 important international academic awards with above-average reputations were identified. Then, based on the number of “awardees in common” or named “co-awardees” between every pair of these 90 awards, a network of co-awardees was built. Finally, using mapping software of VOSviewer, these 90 important international academic awards were mapped by taking the reputation scores as the weights of awards and the network of co-awardees as the basis of the relationships between awards.
Despite nearly 350 years of practice, we still do a fairly poor job of measuring the quality and impact of scholarly papers and the work of individual researchers. Much of our system for determining funding and career advancement revolves around one metric: the impact factor. Technology has progressed to a point where we can do better. We can now track the life of each individual paper after it has been published and better understand how it is read and how it is used. This creates a tremendous opportunity for new alternative metrics (“altmetrics”) to give us a much better sense of a paper's true impact. At the same time, we are now faced with an overwhelming quantity of information and seemingly unlimited ways to analyze a researcher's work. How do we separate out the digital needles from the haystack—the signal from the noise—and create useful tools for research assessment?
Giant academic social networks have taken off to a degree that no one expected even a few years ago. A Nature survey explores why.
Study the past if you would define the future. —Confucius
In 1955, Dr Eugene Garfield published a revolutionary article in Science that forever altered how we measure the impact of scientific articles. In his article, “Citation Indexes for Science: A New Dimension in Documentation Through Association of Ideas,”1 he proposed what would become the Science Citation Index, offering academic journals an Impact Factor (IF) to gauge the importance of their published research.
As I sit here on my MacBook Air in 2014 hearing the ping of new emails and the ding of incoming texts while reading Garfield’s article, which describes early tools like Shepard’s Citations developed in 1873,1 I’m struck by how far we’ve come in 60 years. I think it’s fair to say that prior to drafting a new manuscript, most authors will scour the literature, research via PubMed and PubMed Central, and Google search for redundancy to their own proposed work, asking questions such as: Has someone already tackled this problem? Who was it? When was it? How is my work (potentially) better or more novel? What can I add to the academic literature to justify the publication of this work? The days of singularly consulting print volumes are behind us—the “digital generation” has thrust itself upon us all.
The importance of the IF as a measurement tool cannot be overstated, and we believe in its validity as a gauge to monitor the performance and success of the Aesthetic Surgery Journal ( ASJ ). We will continue our efforts to focus on high-impact articles that will improve the IF score. However, for the past several years, the literature has seen the addition of articles refuting its omnipresence and bemoaning its emphasis on Review articles over new research. The debate over the science and relevance of the IF in …
Phaedra E. Cress, BA, ASAPS, 11262 Monarch St, Garden Grove, CA 92841-1441, USA. E-mail: phaedra{at}surgery.org
Purpose
The purpose of this paper is to examine how often university academic staff members use and create various forms of social media for their work and how that use influences their use of traditional scholarly information sources.
Design/methodology/approach
This article is based on a 2011 academic reading study conducted at six higher learning institutions in the United Kingdom. Approximately 2,000 respondents completed the web‐based survey. The study used the critical incident of last reading by academics to gather information on the purpose, outcomes, and values of scholarly readings and access to library collections. In addition, academics were asked about their use and creation of social media as part of their work activities. The authors looked at six categories of social media – blogs, videos/YouTube, RSS feeds, Twitter feeds, user comments in articles, podcasts, and other. This article focuses on the influence of social media on scholarly reading patterns.
Findings
Most UK academics use one or more forms of social media for work‐related purposes, but creation is less common. Frequency of use and creation is not as high as might be expected, with academics using or creating social media occasionally rather than regularly. There are some differences in use or creation based on demographic factors, including discipline and age. The use and creation of social media does not adversely affect the use of traditional scholarly material, and high frequency users or creators of social media read more scholarly material than others.
Originality/value
This paper illustrates that academics who are engaged with traditional materials for their scholarly work are also embracing various forms of social media to a higher degree than their colleagues. This suggests that social media tools could be a good addition to traditional forms of scholarly content as a way to promote academic growth. Social media is not replacing traditional scholarly material, but rather is enhancing their use.
An extensive analysis of the presence of different altmetric indicators
provided by Altmetric.com across scientific fields is presented, particularly
focusing on their relationship with citations. Our results confirm that the
presence and density of social media altmetric counts are still very low and
not very frequent among scientific publications, with 15%-24% of the
publications presenting some altmetric activity and concentrating in the most
recent publications, although their presence is increasing over time.
Publications from the social sciences, humanities and the medical and life
sciences show the highest presence of altmetrics, indicating their potential
value and interest for these fields. The analysis of the relationships between
altmetrics and citations confirms previous claims of positive correlations but
relatively weak, thus supporting the idea that altmetrics do not reflect the
same concept of impact as citations. Also, altmetric counts do not always
present a better filtering of highly cited publications than journal citation
scores. Altmetrics scores (particularly mentions in blogs) are able to identify
highly cited publications with higher levels of precision than journal citation
scores (JCS), but they have a lower level of recall. The value of altmetrics as
a complementary tool of citation analysis is highlighted, although more
research is suggested to disentangle the potential meaning and value of
altmetric indicators for research evaluation.