Bibliometric analysis with reference publication year spectroscopy showed how key programmes drove developmental care in newborn infants.

AIM: We investigated the historical origins of developmental care for newborn infants using Reference Publication Year Spectroscopy (RPYS), an innovative method of bibliometric analysis. METHODS: A Web of Science search query that combined infant and intervention-related synonyms was performed on 2 February 2022. RPYS analysis was performed on this dataset to identify the most referenced historical publications for developmental care in newborn infants. Median deviation analysis identified the peak publication years, including the most cited historical references. Landmark publications were defined as those belonging to the top 10% of the most frequently referenced publications for at least 20 years. RESULTS: The RPYS peaks showed an early phase (1936-1986), during which infant development was studied and analysed, leading to a conceptualisation of developmental care for newborn infants. The following years (1987-2020), showed an explosion of interest in developmental care and highlighted two main programmes. The Neonatal Individualized Developmental Care Assessment Program (NIDCAP) and the Infant Health and Development Program (IHDP) inspired numerous publications during those years, which strove to demonstrate evidence of their clinical benefits. CONCLUSION: Developmental care has become increasingly important, thanks to the implementation of NIDCAP and IHDP.

How relevant is climate change research for climate change policy? An empirical analysis based on Overton data.

Climate change is an ongoing topic in nearly all areas of society since many years. A discussion of climate change without referring to scientific results is not imaginable. This is especially the case for policies since action on the macro scale is required to avoid costly consequences for society. In this study, we deal with the question of how research on climate change and policy are connected. In 2019, the new Overton database of policy documents was released including links to research papers that are cited by policy documents. The use of results and recommendations from research on climate change might be reflected in citations of scientific papers in policy documents. Although we suspect a lot of uncertainty related to the coverage of policy documents in Overton, there seems to be an impact of international climate policy cycles on policy document publication. We observe local peaks in climate policy documents around major decisions in international climate diplomacy. Our results point out that IGOs and think tanks-with a focus on climate change-have published more climate change policy documents than expected. We found that climate change papers that are cited in climate change policy documents received significantly more citations on average than climate change papers that are not cited in these documents. Both areas of society (science and policy) focus on similar climate change research fields: biology, earth sciences, engineering, and disease sciences. Based on these and other empirical results in this study, we propose a simple model of policy impact considering a chain of different document types: The chain starts with scientific assessment reports (systematic reviews) that lead via science communication documents (policy briefs, policy reports or plain language summaries) and government reports to legislative documents.

On Health Effects of Resveratrol in Wine.

We analyzed 3344 publications concerned with the health-related effects of resveratrol that occurs in wine and grapes. We discovered that publication activity increased until 2010 and decreased slightly afterwards. The most frequent author keywords were classified into six groups: (1) beverage-related keywords, (2) compound-related keywords, (3) disease-related keywords, (4) effect-related keywords, (5) mechanism-related keywords, and (6) broader keywords. By means of reference publication year spectroscopy, we analyzed and discussed the most frequently cited references (i.e., key papers) within the publication set. A rather large portion of the key papers exhibit a deliberative or positive attitude and report on the health effects of resveratrol, although limited data in humans preclude drawing unambiguous conclusions on its health-related benefits. From our analysis, we could not identify specific publications that provide a distinct change of direction of the ongoing scientific discourse. Moderate red wine consumption seems to bear the potential of being health promoting, whereas excessive alcohol consumption can induce liver cirrhosis and cancer.

Heat waves: a hot topic in climate change research.

Research on heat waves (periods of excessively hot weather, which may be accompanied by high humidity) is a newly emerging research topic within the field of climate change research with high relevance for the whole of society. In this study, we analyzed the rapidly growing scientific literature dealing with heat waves. No summarizing overview has been published on this literature hitherto. We developed a suitable search query to retrieve the relevant literature covered by the Web of Science (WoS) as complete as possible and to exclude irrelevant literature (n = 8,011 papers). The time evolution of the publications shows that research dealing with heat waves is a highly dynamic research topic, doubling within about 5 years. An analysis of the thematic content reveals the most severe heat wave events within the recent decades (1995 and 2003), the cities and countries/regions affected (USA, Europe, and Australia), and the ecological and medical impacts (drought, urban heat islands, excess hospital admissions, and mortality). An alarming finding is that the limit for survivability may be reached at the end of the twenty-first century in many regions of the world due to the fatal combination of rising temperatures and humidity levels measured as "wet-bulb temperature" (WBT). Risk estimation and future strategies for adaptation to hot weather are major political issues. We identified 104 citation classics, which include fundamental early works of research on heat waves and more recent works (which are characterized by a relatively strong connection to climate change).

Can tweets be used to detect problems early with scientific papers? A case study of three retracted COVID-19/SARS-CoV-2 papers.

Methodological mistakes, data errors, and scientific misconduct are considered prevalent problems in science that are often difficult to detect. In this study, we explore the potential of using data from Twitter for discovering problems with publications. In this case study, we analyzed tweet texts of three retracted publications about COVID-19 (Coronavirus disease 2019)/SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) and their retraction notices. We did not find early warning signs in tweet texts regarding one publication, but we did find tweets that casted doubt on the validity of the two other publications shortly after their publication date. An extension of our current work might lead to an early warning system that makes the scientific community aware of problems with certain publications. Other sources, such as blogs or post-publication peer-review sites, could be included in such an early warning system. The methodology proposed in this case study should be validated using larger publication sets that also include a control group, i.e., publications that were not retracted.

A call for governments to pause Twitter censorship: using Twitter data as social-spatial sensors of COVID-19/SARS-CoV-2 research diffusion.

In this study we determined whether Twitter data can be used as social-spatial sensors to show how research on COVID-19/SARS-CoV-2 diffuses through the population to reach the people that are affected by the disease. We performed a cross-sectional bibliometric analysis between 23rd March and 14th April 2020. Three sources of data were used: (1) deaths per number of population for COVID-19/SARS-CoV-2 retrieved from John Hopkins University and Worldometer, (2) publications related to COVID-19/SARS-CoV-2 retrieved from World Health Organisation COVID-19 database, and (3) tweets of these publications retrieved from Altmetric.com and Twitter. In the analysis, the number of publications used was 1761, and number of tweets used was 751,068. Mapping of worldwide data illustrated that high Twitter activity was related to high numbers of COVID-19/SARS-CoV-2 deaths, with tweets inversely weighted with number of publications. Regression models of worldwide data showed a positive correlation between the national deaths per number of population and tweets when holding number of publications constant (coefficient 0.0285, S.E. 0.0003, p < 0.001). Twitter can play a crucial role in the rapid research response during the COVID-19/SARS-CoV-2 pandemic, especially to spread research with prompt public scrutiny. Governments are urged to pause censorship of social media platforms to support the scientific community's fight against COVID-19/SARS-CoV-2.

Are papers addressing certain diseases perceived where these diseases are prevalent? The proposal to use Twitter data as social-spatial sensors.

We propose to use Twitter data as social-spatial sensors. This study deals with the question whether research papers on certain diseases are perceived by people in regions (worldwide) that are especially concerned by these diseases. Since (some) Twitter data contain location information, it is possible to spatially map the activity of Twitter users referring to certain papers (e.g., dealing with tuberculosis). The resulting maps reveal whether heavy activity on Twitter is correlated with large numbers of people having certain diseases. In this study, we focus on tuberculosis, human immunodeficiency virus (HIV), and malaria, since the World Health Organization ranks these diseases as the top three causes of death worldwide by a single infectious agent. The results of the social-spatial Twitter maps (and additionally performed regression models) reveal the usefulness of the proposed sensor approach. One receives an impression of how research papers on the diseases have been perceived by people in regions that are especially concerned by these diseases. Our study demonstrates a promising approach for using Twitter data for research evaluation purposes beyond simple counting of tweets.

Influential cited references in FEMS Microbiology Letters: lessons from Reference Publication Year Spectroscopy (RPYS).

The journal FEMS Microbiology Letters covers all aspects of microbiology including virology. On which scientific shoulders do the papers published in this journal stand? Which are the classic papers used by the authors? We aim to answer these questions in this study by applying the Reference Publication Year Spectroscopy (RPYS) analysis to all papers published in this journal between 1977 and 2017. In total, 16 837 publications with 410 586 cited references are analyzed. Mainly, the studies published in the journal FEMS Microbiology Letters draw knowledge from methods developed to quantify or characterize biochemical substances such as proteins, nucleic acids, lipids, or carbohydrates and from improvements of techniques suitable for studies of bacterial genetics. The techniques frequently used for studying the genetic of microorganisms in FEMS Microbiology Letters' studies were developed using samples prepared from microorganisms. Methods required for the investigation of proteins, carbohydrates, or lipids were mostly transferred from other fields of life science to microbiology.

A comprehensive analysis of the history of DFT based on the bibliometric method RPYS.

This bibliometric study aims at providing a comprehensive analysis of the history of density functional theory (DFT) from a perspective of chemistry by using reference publication year spectroscopy (RPYS). 114,138 publications with their 4,412,152 non-distinct cited references are analyzed. The RPYS analysis revealed three different groups of seminal papers which researchers in DFT have drawn from: (i) some long-known experimental studies from the 19th century about physical and chemical phenomena were referenced rather frequently in contemporary DFT publications. (ii) Fundamental quantum-chemical papers from the time period 1900-1950 which predate DFT form another group of seminal papers. (iii) Finally, various very frequently employed DFT approximations, basis sets, and other techniques (e.g., implicit descriptions of solvents) constitute another group of seminal papers. The earliest cited reference we found was published in 1806. The references to papers published in the 19th century mainly served the purpose of referring to long-known physical and chemical phenomena which were used to test if DFT approximations deliver correct results (e.g., Van der Waals interactions). The foundational papers of DFT by Hohenberg and Kohn as well as Kohn and Sham do not seem to be affected by obliteration by incorporation as they appear as pronounced peaks in our RPYS analysis. Since the 1990s, only very few pronounced peaks occur as most years were referenced nearly equally often. Exceptions are 1993 and 1996 due to seminal papers by Axel Becke, John P. Perdew and co-workers, and Georg Kresse and co-workers.

Field- and time-normalization of data with many zeros: an empirical analysis using citation and Twitter data.

Thelwall (J Informetr 11(1):128-151, 2017a. 10.1016/j.joi.2016.12.002; Web indicators for research evaluation: a practical guide. Morgan and Claypool, London, 2017b) proposed a new family of field- and time-normalized indicators, which is intended for sparse data. These indicators are based on units of analysis (e.g., institutions) rather than on the paper level. They compare the proportion of mentioned papers (e.g., on Twitter) of a unit with the proportion of mentioned papers in the corresponding fields and publication years. We propose a new indicator (Mantel-Haenszel quotient, MHq) for the indicator family. The MHq is rooted in the Mantel-Haenszel (MH) analysis. This analysis is an established method, which can be used to pool the data from several 2 × 2 cross tables based on different subgroups. We investigate using citations and assessments by peers whether the indicator family can distinguish between quality levels defined by the assessments of peers. Thus, we test the convergent validity. We find that the MHq is able to distinguish between quality levels in most cases while other indicators of the family are not. Since our study approves the MHq as a convergent valid indicator, we apply the MHq to four different Twitter groups as defined by the company Altmetric. Our results show that there is a weak relationship between the Twitter counts of all four Twitter groups and scientific quality, much weaker than between citations and scientific quality. Therefore, our results discourage the use of Twitter counts in research evaluation.

Do altmetrics correlate with the quality of papers? A large-scale empirical study based on F1000Prime data.

In this study, we address the question whether (and to what extent, respectively) altmetrics are related to the scientific quality of papers (as measured by peer assessments). Only a few studies have previously investigated the relationship between altmetrics and assessments by peers. In the first step, we analyse the underlying dimensions of measurement for traditional metrics (citation counts) and altmetrics-by using principal component analysis (PCA) and factor analysis (FA). In the second step, we test the relationship between the dimensions and quality of papers (as measured by the post-publication peer-review system of F1000Prime assessments)-using regression analysis. The results of the PCA and FA show that altmetrics operate along different dimensions, whereas Mendeley counts are related to citation counts, and tweets form a separate dimension. The results of the regression analysis indicate that citation-based metrics and readership counts are significantly more related to quality, than tweets. This result on the one hand questions the use of Twitter counts for research evaluation purposes and on the other hand indicates potential use of Mendeley reader counts.

Measuring Individual Performance with Comprehensive Bibliometric Reports as an Alternative to h-Index Values.

The h-index is frequently used to measure the performance of single scientists in Korea (and beyond). No single indicator alone, however, is able to provide a stable and complete assessment of performance. The Stata command bibrep.ado is introduced which automatically produces bibliometric reports for single researchers (senior researchers working in the natural or life sciences). The user of the command receives a comprehensive bibliometric report which can be used in research evaluation instead of the h-index.

Plots for visualizing paper impact and journal impact of single researchers in a single graph.

In research evaluation of single researchers, the assessment of paper and journal impact is of interest. High journal impact reflects the ability of researchers to convince strict reviewers, and high paper impact reflects the usefulness of papers for future research. In many bibliometric studies, metrics for journal and paper impact are separately presented. In this paper, we introduce two graph types, which combine both metrics in a single graph. The graphs can be used in research evaluation to visualize the performance of single researchers comprehensively.

Visualizing the context of citations referencing papers published by Eugene Garfield: a new type of keyword co-occurrence analysis.

During Eugene Garfield's (EG's) lengthy career as information scientist, he published about 1500 papers. In this study, we use the impressive oeuvre of EG to introduce a new type of bibliometric networks: keyword co-occurrences networks based on the context of citations, which are referenced in a certain paper set (here: the papers published by EG). The citation context is defined by the words which are located around a specific citation. We retrieved the citation context from Microsoft Academic. To interpret and compare the results of the new network type, we generated two further networks: co-occurrence networks which are based on title and abstract keywords from (1) EG's papers and (2) the papers citing EG's publications. The comparison of the three networks suggests that papers of EG and citation contexts of papers citing EG are semantically more closely related to each other than to titles and abstracts of papers citing EG. This result accords with the use of citations in research evaluation that is based on the premise that citations reflect the cognitive influence of the cited on the citing publication.

Reference publication year spectroscopy (RPYS) of Eugene Garfield's publications.

Which studies, theories, and ideas have influenced Eugene Garfield's scientific work? Recently, the method reference publication year spectroscopy (RPYS) has been introduced, which can be used to answer this and related questions. Since then, several studies have been published dealing with the historical roots of research fields and scientists. The program CRExplorer (http://www.crexplorer.net) was specifically developed for RPYS. In this study, we use this program to investigate the historical roots of Eugene Garfield's oeuvre.

Slow reception and under-citedness in climate change research: A case study of Charles David Keeling, discoverer of the risk of global warming.

The Keeling curve has become a chemical landmark, whereas the papers by Charles David Keeling about the underlying carbon dioxide measurements are not cited as often as can be expected against the backdrop of his final approval. In this bibliometric study, we analyze Keeling's papers as a case study for under-citedness of climate change publications. Three possible reasons for the under-citedness of Keeling's papers are discussed: (1) The discourse on global cooling at the starting time of Keeling's measurement program, (2) the underestimation of what is often seen as "routine science", and (3) the amount of implicit/informal citations at the expense of explicit/formal (reference-based) citations. Those reasons may have contributed more or less to the slow reception and the under-citedness of Keeling's seminal works.

How many scientific papers are mentioned in policy-related documents? An empirical investigation using Web of Science and Altmetric data.

In this short communication, we provide an overview of a relatively newly provided source of altmetrics data which could possibly be used for societal impact measurements in scientometrics. Recently, Altmetric-a start-up providing publication level metrics-started to make data for publications available which have been mentioned in policy-related documents. Using data from Altmetric, we study how many papers indexed in the Web of Science (WoS) are mentioned in policy-related documents. We find that less than 0.5% of the papers published in different subject categories are mentioned at least once in policy-related documents. Based on our results, we recommend that the analysis of (WoS) publications with at least one policy-related mention is repeated regularly (annually) in order to check the usefulness of the data. Mentions in policy-related documents should not be used for impact measurement until new policy-related sites are tracked.

Which early works are cited most frequently in climate change research literature? A bibliometric approach based on Reference Publication Year Spectroscopy.

This bibliometric analysis focuses on the general history of climate change research and, more specifically, on the discovery of the greenhouse effect. First, the Reference Publication Year Spectroscopy (RPYS) is applied to a large publication set on climate change of 222,060 papers published between 1980 and 2014. The references cited therein were extracted and analyzed with regard to publications, which are cited most frequently. Second, a new method for establishing a more subject-specific publication set for applying RPYS (based on the co-citations of a marker reference) is proposed (RPYS-CO). The RPYS of the climate change literature focuses on the history of climate change research in total. We identified 35 highly-cited publications across all disciplines, which include fundamental early scientific works of the nineteenth century (with a weak connection to climate change) and some cornerstones of science with a stronger connection to climate change. By using the Arrhenius (Philos Mag J Sci Ser 5(41):237-276, 1896) paper as a RPYS-CO marker paper, we selected only publications specifically discussing the discovery of the greenhouse effect and the role of carbon dioxide. Using different RPYS approaches in this study, we were able to identify the complete range of works of the celebrated icons as well as many less known works relevant for the history of climate change research. The analyses confirmed the potential of the RPYS method for historical studies: Seminal papers are detected on the basis of the references cited by the overall community without any further assumptions.

Does evaluative scientometrics lose its main focus on scientific quality by the new orientation towards societal impact?

When the meaning of key terms is incompatible in competing taxonomies, a revolution might occur in the field by which the established taxonomy is replaced with another. Since the key term "impact" in scientometrics seems to undergo a taxonomic change, a revolution might be taking place at present: Impact is no longer defined as impact on science alone (measured by citations), but on all sectors of society (e.g. economics, culture, or politics). In this Short Communication, we outline that the current revolution in scientometrics does not only imply a broadening of the impact perspective, but also the devaluation of quality considerations in evaluative contexts. Impact might no longer be seen as a proxy for quality, but in its original sense: the simple resonance in some sectors of society.