The Citation Wake of Publications Detects Nobel Laureates' Papers

For several decades, a leading paradigm of how to quantitatively assess scientific research has been the analysis of the aggregated citation information in a set of scientific publications. Although the representation of this information as a citation network has already been coined in the 1960s, it needed the systematic indexing of scientific literature to allow for impact metrics that actually made use of this network as a whole, improving on the then prevailing metrics that were almost exclusively based on the number of direct citations. However, besides focusing on the assignment of credit, the paper citation network can also be studied in terms of the proliferation of scientific ideas. Here we introduce a simple measure based on the shortest-paths in the paper''s in-component or, simply speaking, on the shape and size of the wake of a paper within the citation network. Applied to a citation network containing Physical Review publications from more than a century, our approach is able to detect seminal articles which have introduced concepts of obvious importance to the further development of physics. We observe a large fraction of papers co-authored by Nobel Prize laureates in physics among the top-ranked publications.     

A simple index for the high-citation tail of citation distribution to quantify research performance in countries and institutions

Background

Conventional scientometric predictors of research performance such as the number of papers, citations, and papers in the top 1% of highly cited papers cannot be validated in terms of the number of Nobel Prize achievements across countries and institutions. The purpose of this paper is to find a bibliometric indicator that correlates with the number of Nobel Prize achievements.

Methodology/Principal Findings

This study assumes that the high-citation tail of citation distribution holds most of the information about high scientific performance. Here I propose the x-index, which is calculated from the number of national articles in the top 1% and 0.1% of highly cited papers and has a subtractive term to discount highly cited papers that are not scientific breakthroughs. The x-index, the number of Nobel Prize achievements, and the number of national articles in Nature or Science are highly correlated. The high correlations among these independent parameters demonstrate that they are good measures of high scientific performance because scientific excellence is their only common characteristic. However, the x-index has superior features as compared to the other two parameters. Nobel Prize achievements are low frequency events and their number is an imprecise indicator, which in addition is zero in most institutions; the evaluation of research making use of the number of publications in prestigious journals is not advised.

Conclusion

The x-index is a simple and precise indicator for high research performance.     

Multiple Citation Indicators and Their Composite across Scientific Disciplines

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.     

The use of scientometric parameters for the evaluation of scientific contributions

This paper deals with the application of scientometric parameters in the evaluation of scientists, either as individuals or in small formal groups. The parameters are divided into two groups: parameters of scientific productivity and citation parameters. The scientific productivity was further subdivided into three types of parameters: (i) total productivity, (ii) partial productivity, and (iii) productivity in scientific fields and subfields. These citation parameters were considered: (i) impact factors of journals, (ii) impact factors of scientific fields and subfields, (iii) citations of individual papers, (iv) citations of individual authors, (v) expected citation rates and relative citation rates, and (vi) self-citations, independent citations and negative citations. Particular attention was payed to the time-dependence of the scientometric parameters. If available, numeric values of the world parameters were given and compared with the data about the scientific output of Croatian scientists.     

The Scientific Impact of Nations: Journal Placement and Citation Performance

International collaboration is becoming increasingly important for the advancement of science. To gain a more precise understanding of how factors such as international collaboration influence publication success, we divide publication success into two categories: journal placement and citation performance. Analyzing all papers published between 1996 and 2012 in eight disciplines, we find that those with more countries in their affiliations performed better in both categories. Furthermore, specific countries vary in their effects both individually and in combination. Finally, we look at the relationship between national output (in papers published) and input (in citations received) over the 17 years, expanding upon prior depictions by also plotting an expected proportion of citations based on Journal Placement. Discrepancies between this expectation and the realized proportion of citations illuminate trends in performance, such as the decline of the Global North in response to rapidly developing countries, especially China. Yet, most countries'' show little to no discrepancy, meaning that, in most cases, citation proportion can be predicted by Journal Placement alone. This reveals an extreme asymmetry between the opinions of a few reviewers and the degree to which paper acceptance and citation rates influence career advancement.     

Fifty-Year Fate and Impact of General Medical Journals

Background

Influential medical journals shape medical science and practice and their prestige is usually appraised by citation impact metrics, such as the journal impact factor. However, how permanent are medical journals and how stable is their impact over time?

Methods and Results

We evaluated what happened to general medical journals that were publishing papers half a century ago, in 1959. Data were retrieved from ISI Web of Science for citations and PubMed (Journals function) for journal history. Of 27 eligible journals publishing in 1959, 4 have stopped circulation (including two of the most prestigious journals in 1959) and another 7 changed name between 1959 and 2009. Only 6 of these 27 journals have been published continuously with their initial name since they started circulation. The citation impact of papers published in 1959 gives a very different picture from the current journal impact factor; the correlation between the two is non-significant and very close to zero. Only 13 of the 5,223 papers published in 1959 received at least 5 citations in 2009.

Conclusions

Journals are more permanent entities than single papers, but they are also subject to major change and their relative prominence can change markedly over time.     

The Measurement of the Effect on Citation Inequality of Differences in Citation Practices across Scientific Fields

This paper has two aims: (i) to introduce a novel method for measuring which part of overall citation inequality can be attributed to differences in citation practices across scientific fields, and (ii) to implement an empirical strategy for making meaningful comparisons between the number of citations received by articles in 22 broad fields. The number of citations received by any article is seen as a function of the article’s scientific influence, and the field to which it belongs. A key assumption is that articles in the same quantile of any field citation distribution have the same degree of citation impact in their respective field. Using a dataset of 4.4 million articles published in 1998–2003 with a five-year citation window, we estimate that differences in citation practices between the 22 fields account for 14% of overall citation inequality. Our empirical strategy is based on the strong similarities found in the behavior of citation distributions. We obtain three main results. Firstly, we estimate a set of average-based indicators, called exchange rates, to express the citations received by any article in a large interval in terms of the citations received in a reference situation. Secondly, using our exchange rates as normalization factors of the raw citation data reduces the effect of differences in citation practices to, approximately, 2% of overall citation inequality in the normalized citation distributions. Thirdly, we provide an empirical explanation of why the usual normalization procedure based on the fields’ mean citation rates is found to be equally successful.     

A possible role of social activity to explain differences in publication output among ecologists

Publication output is the standard by which scientific productivity is evaluated. Despite a plethora of papers on the issue of publication and citation biases, no study has so far considered a possible effect of social activities on publication output. One of the most frequent social activities in the world is drinking alcohol. In Europe, most alcohol is consumed as beer and, based on well known negative effects of alcohol consumption on cognitive performance, I predicted negative correlations between beer consumption and several measures of scientific performance. Using a survey from the Czech Republic, that has the highest per capita beer consumption rate in the world, I show that increasing per capita beer consumption is associated with lower numbers of papers, total citations, and citations per paper (a surrogate measure of paper quality). In addition I found the same predicted trends in comparison of two separate geographic areas within the Czech Republic that are also known to differ in beer consumption rates. These correlations are consistent with the possibility that leisure time social activities might influence the quality and quantity of scientific work and may be potential sources of publication and citation biases.     

Citation Classics in Systematic Reviews and Meta-Analyses: Who Wrote the Top 100 Most Cited Articles?

Background

Systematic reviews of the literature occupy the highest position in currently proposed hierarchies of evidence. The aims of this study were to assess whether citation classics exist in published systematic review and meta-analysis (SRM), examine the characteristics of the most frequently cited SRM articles, and evaluate the contribution of different world regions.

Methods

The 100 most cited SRM were identified in October 2012 using the Science Citation Index database of the Institute for Scientific Information. Data were extracted by one author. Spearman’s correlation was used to assess the association between years since publication, numbers of authors, article length, journal impact factor, and average citations per year.

Results

Among the 100 citation classics, published between 1977 and 2008, the most cited article received 7308 citations and the least-cited 675 citations. The average citations per year ranged from 27.8 to 401.6. First authors from the USA produced the highest number of citation classics (n=46), followed by the UK (n=28) and Canada (n=15). The 100 articles were published in 42 journals led by the Journal of the American Medical Association (n=18), followed by the British Medical Journal (n=14) and The Lancet (n=13). There was a statistically significant positive correlation between number of authors (Spearman’s rho=0.320, p=0.001), journal impact factor (rho=0.240, p=0.016) and average citations per year. There was a statistically significant negative correlation between average citations per year and year since publication (rho = -0.636, p=0.0001). The most cited papers identified seminal contributions and originators of landmark methodological aspects of SRM and reflect major advances in the management of and predisposing factors for chronic diseases.

Conclusions

Since the late 1970s, the USA, UK, and Canada have taken leadership in the production of citation classic papers. No first author from low or middle-income countries (LMIC) led one of the most cited 100 SRM.     

Incorrect Citations Give Unfair Credit to Review Authors in Ecology Journals

The number of citations that papers receive has become significant in measuring researchers'' scientific productivity, and such measurements are important when one seeks career opportunities and research funding. Skewed citation practices can thus have profound effects on academic careers. We investigated (i) how frequently authors misinterpret original information and (ii) how frequently authors inappropriately cite reviews instead of the articles upon which the reviews are based. To reach this aim, we carried a survey of ecology journals indexed in the Web of Science and assessed the appropriateness of citations of review papers. Reviews were significantly more often cited than regular articles. In addition, 22% of citations were inaccurate, and another 15% unfairly gave credit to the review authors for other scientists'' ideas. These practices should be stopped, mainly through more open discussion among mentors, researchers and students.     

Long-Distance Interdisciplinarity Leads to Higher Scientific Impact

Scholarly collaborations across disparate scientific disciplines are challenging. Collaborators are likely to have their offices in another building, attend different conferences, and publish in other venues; they might speak a different scientific language and value an alien scientific culture. This paper presents a detailed analysis of success and failure of interdisciplinary papers—as manifested in the citations they receive. For 9.2 million interdisciplinary research papers published between 2000 and 2012 we show that the majority (69.9%) of co-cited interdisciplinary pairs are “win-win” relationships, i.e., papers that cite them have higher citation impact and there are as few as 3.3% “lose-lose” relationships. Papers citing references from subdisciplines positioned far apart (in the conceptual space of the UCSD map of science) attract the highest relative citation counts. The findings support the assumption that interdisciplinary research is more successful and leads to results greater than the sum of its disciplinary parts.     

A reverse engineering approach to the suppression of citation biases reveals universal properties of citation distributions

The large amount of information contained in bibliographic databases has recently boosted the use of citations, and other indicators based on citation numbers, as tools for the quantitative assessment of scientific research. Citations counts are often interpreted as proxies for the scientific influence of papers, journals, scholars, and institutions. However, a rigorous and scientifically grounded methodology for a correct use of citation counts is still missing. In particular, cross-disciplinary comparisons in terms of raw citation counts systematically favors scientific disciplines with higher citation and publication rates. Here we perform an exhaustive study of the citation patterns of millions of papers, and derive a simple transformation of citation counts able to suppress the disproportionate citation counts among scientific domains. We find that the transformation is well described by a power-law function, and that the parameter values of the transformation are typical features of each scientific discipline. Universal properties of citation patterns descend therefore from the fact that citation distributions for papers in a specific field are all part of the same family of univariate distributions.     

Contribution of case reports to brain metastases research: systematic review and analysis of pattern of citation

Research activity related to different aspects of prevention, prediction, diagnosis and treatment of brain metastases has increased during recent years. One of the major databases (Scopus) contains 942 scientific articles that were published during the 5-year time period 2006–2010. Of these, 195 (21%) reported on single patient cases and 12 (1%) were reports of 2 cases. Little is known about their influence on advancement of the field or scientific merits. Do brain metastases case reports attract attention and provide stimuli for further research or do they go largely unrecognized? Different measures of impact, visibility and quality of published research are available, each with its own pros and cons. For the present evaluation, article citation rate was chosen. The median number of citations overall and stratified by year of publication was 0, except for the year 2006 when it was 2. As compared to other articles, case reports remained more often without citation (p<0.05 except for 2006 data). All case reports with 10 or more citations (n = 6) reported on newly introduced anticancer drugs, which commonly are prescribed to treat extracranial metastases, and the responses observed in single patients with brain metastases. Average annual numbers of citations were also calculated. The articles with most citations per year were the same six case reports mentioned above (the only ones that obtained more than 2.0 citations per year). Citations appeared to gradually increase during the first two years after publication but remained on a generally low or modest level. It cannot be excluded that case reports without citation provide interesting information to some clinicians or researchers. Apparently, case reports describing unexpected therapeutic success gain more attention, at least in terms of citation, than others.     

Flawed citation practices facilitate the unsubstantiated perception of a global trend toward increased jellyfish blooms

Speculation over a global rise in jellyfish populations has become widespread in the scientific literature, but until recently the purported ‘global increase’ had not been tested. Here we present a citation analysis of peer‐reviewed literature to track the evolution of the current perception of increases in jellyfish and identify key papers involved in its establishment. Trend statements and citation threads were reviewed and arranged in a citation network. Trend statements were assessed according their degree of affirmation and spatial scale, and the appropriateness of the citations used to support statements was assessed. Analyses showed that 48.9% of publications misinterpreted the conclusions of cited sources, with a bias towards claiming jellyfish populations are increasing, with a single review having the most influence on the network. Collectively, these disparities resulted in a network based on unsubstantiated statements and citation threads. As a community, we must ensure our statements about scientific findings in general are accurately substantiated and carefully communicated such that incorrect perceptions, as in the case of jellyfish blooms, do not develop in the absence of rigorous testing.     

Systematic Differences in Impact across Publication Tracks at PNAS

Background

Citation data can be used to evaluate the editorial policies and procedures of scientific journals. Here we investigate citation counts for the three different publication tracks of the Proceedings of the National Academy of Sciences of the United States of America (PNAS). This analysis explores the consequences of differences in editor and referee selection, while controlling for the prestige of the journal in which the papers appear.

Methodology/Principal Findings

We find that papers authored and “Contributed” by NAS members (Track III) are on average cited less often than papers that are “Communicated” for others by NAS members (Track I) or submitted directly via the standard peer review process (Track II). However, we also find that the variance in the citation count of Contributed papers, and to a lesser extent Communicated papers, is larger than for direct submissions. Therefore when examining the 10% most-cited papers from each track, Contributed papers receive the most citations, followed by Communicated papers, while Direct submissions receive the least citations.

Conclusion/Significance

Our findings suggest that PNAS “Contributed” papers, in which NAS–member authors select their own reviewers, balance an overall lower impact with an increased probability of publishing exceptional papers. This analysis demonstrates that different editorial procedures are associated with different levels of impact, even within the same prominent journal, and raises interesting questions about the most appropriate metrics for judging an editorial policy''s success.     

Contribution of Genome-Wide Association Studies to Scientific Research: A Bibliometric Survey of the Citation Impacts of GWAS and Candidate Gene Studies Published during the Same Period and in the Same Journals

In genetic epidemiology, genome-wide association studies (GWAS) are used to rapidly scan a large set of genetic variants and thus to identify associations with a particular trait or disease. The GWAS philosophy is different to that of conventional candidate-gene-based approaches, which directly test the effects of genetic variants of potentially contributory genes in an association study. One controversial question is whether GWAS provide relevant scientific outcomes by comparison with candidate-gene studies. We thus performed a bibliometric study using two citation metrics to assess whether the GWAS have contributed a capital gain in knowledge discovery by comparison with candidate-gene approaches. We selected GWAS published between 2005 and 2009 and matched them with candidate-gene studies on the same topic and published in the same period of time. We observed that the GWAS papers have received, on average, 30±55 citations more than the candidate gene papers, 1 year after their publication date, and 39±58 citations more 2 years after their publication date. The GWAS papers were, on average, 2.8±2.4 and 2.9±2.4 times more cited than expected, 1 and 2 years after their publication date; whereas the candidate gene papers were 1.5±1.2 and 1.5±1.4 times more cited than expected. While the evaluation of the contribution to scientific research through citation metrics may be challenged, it cannot be denied that GWAS are great hypothesis generators, and are a powerful complement to candidate gene studies.     

Using Noun Phrases for Navigating Biomedical Literature on Pubmed: How Many Updates Are We Losing Track of?

Author-supplied citations are a fraction of the related literature for a paper. The "related citations" on PubMed is typically dozens or hundreds of results long, and does not offer hints why these results are related. Using noun phrases derived from the sentences of the paper, we show it is possible to more transparently navigate to PubMed updates through search terms that can associate a paper with its citations. The algorithm to generate these search terms involved automatically extracting noun phrases from the paper using natural language processing tools, and ranking them by the number of occurrences in the paper compared to the number of occurrences on the web. We define search queries having at least one instance of overlap between the author-supplied citations of the paper and the top 20 search results as citation validated (CV). When the overlapping citations were written by same authors as the paper itself, we define it as CV-S and different authors is defined as CV-D. For a systematic sample of 883 papers on PubMed Central, at least one of the search terms for 86% of the papers is CV-D versus 65% for the top 20 PubMed "related citations." We hypothesize these quantities computed for the 20 million papers on PubMed to differ within 5% of these percentages. Averaged across all 883 papers, 5 search terms are CV-D, and 10 search terms are CV-S, and 6 unique citations validate these searches. Potentially related literature uncovered by citation-validated searches (either CV-S or CV-D) are on the order of ten per paper--many more if the remaining searches that are not citation-validated are taken into account. The significance and relationship of each search result to the paper can only be vetted and explained by a researcher with knowledge of or interest in that paper.     

Genealogical Trees of Scientific Papers

Many results have been obtained when studying scientific papers citations databases in a network perspective. Articles can be ranked according to their current in-degree and their future popularity or citation counts can even be predicted. The dynamical properties of such networks and the observation of the time evolution of their nodes started more recently. This work adopts an evolutionary perspective and proposes an original algorithm for the construction of genealogical trees of scientific papers on the basis of their citation count evolution in time. The fitness of a paper now amounts to its in-degree growing trend and a “dying” paper will suddenly see this trend declining in time. It will give birth and be taken over by some of its most prevalent citing “offspring”. Practically, this might be used to trace the successive published milestones of a research field.     

论文引用率影响因素——中外生态学期刊比较

本文选择8种有代表性中外生态学期刊,对其一定发表周期内的论文引用率进行分析,探讨生态学论文引用率的影响因素及中外生态学期刊的差异.结果表明：4种英文期刊的年均被引次数均远大于4种中文期刊;英文期刊1位作者的论文数量百分比相对较高;所有期刊的合著论文比例均较高,体现了合作性在现代生态学研究中的重要性;论文作者数量与引用率之间有一定的正相关关系,但不显著;英文期刊论文的长度显著高于中文论文;随着论文长度的增加,年均被引次数增多.对中外期刊论文的引用率变化动态进行分析表明,英文期刊中总被引次数高的论文其增长速率也较快,表明其持续影响力强于中文生态学论文.我们希望这些结果会对生态学者以及相关期刊工作者有所裨益.