The sum of it all: Revealing collaboration patterns by combining authorship and acknowledgements

Impact of medical technologies may be predicted using constructed graph bibliometrics

Scientific research is driven by allocation of funding to different research projects based in part on the predicted scientific impact of the work. Data-driven algorithms can inform decision-making of scarce funding resources by identifying likely high-impact studies using bibliometrics. Compared to standardized citation-based metrics alone, we utilize a machine learning pipeline that analyzes high-dimensional relationships among a range of bibliometric features to improve the accuracy of predicting high-impact research. Random forest classification models were trained using 28 bibliometric features calculated from a dataset of 1,485,958 publications in medicine to retrospectively predict whether a publication would become high-impact. For each random forest model, the balanced accuracy score was above 0.95 and the area under the receiver operating characteristic curve was above 0.99. The high performance of high impact research prediction using our proposed models show that machine learning technologies are promising algorithms that can support funding decision-making for medical research.

From art to science: A bibliometric analysis of architectural scholarly production from 1980 to 2015

According to recent literature on “architecture” as a discipline, practical knowledge relevant to its process of making has decreased in importance in favor of a more academic approach. Using data derived from Ulrich’s Periodical Directory and Clarivate Analytics’s Web of Science, this paper suggests providing empirical evidence supporting of such shift, as revealed by an overview of the dissemination practices in architecture scholarly production between 1980 and 2015. Our results support that architecture is becoming increasingly academic, as demonstrated by the growing proportion of articles and journals intended for scholars rather than for professionals. We also show that architecture is increasingly global, with decreased interest in local and/or national issues and the growing prevalence of English as a publication language. Finally, this academic focus is manifested in references cited by architectural papers with the gradual substitution of professional and artistic oriented knowledge, for scientific approaches tied to engineering and technology.

Dataset of identified scholars mentioned in acknowledgement statements

Acknowledgements represent scholars' relationships as part of the research contribution. While co-authors and citations are often provided as a well-formatted bibliometric database, acknowledged individuals are difficult to identify because they appear as part of the statements in the paper. We identify acknowledged scholars who appeared in papers published in open-access journals by referring to the co-author and citation relationships stored in the Microsoft Academic Graph (MAG). Therefore, the constructed dataset is compatible with MAG, which accelerates and expands the acknowledgements as a data source of scholarly relationships similar to collaboration and citation analysis. Moreover, the implemented code is publicly available; thus, it can be applied in other studies.

Authorship in the Medical Humanities: Breaking Cross-field Boundaries or Maintaining Disciplinary Divides?

PURPOSE

Medical humanities is a field which implies collaborative work across disciplines although the degree to which this actually occurs is unknown. Our purpose was to determine the degree of joint work in medical humanities through analysis of authorship and acknowledgements in the two main medical humanities journals.

METHODS

Observational survey of authorship. We studied authorship data in all papers published in the two major general medical humanities journals between 2009 and 2018 (n=595).

RESULTS

Two-thirds of papers (67.4%) had single authors, of whom a majority declared a single disciplinary affiliation (70.3%). The titles of 60.8% of papers explicitly suggested collaborative content of which 19.9% had multiple authors from more than one discipline (not within the same school); of the remainder, almost half (48.1%) had a single, single-disciplinary author (although 8.5% demonstrated interdisciplinarity in the acknowledgements). One-third of papers (193/595;33%) referenced one or more people in the acknowledgements. Among papers whose titles suggested humanities or medical content only, authorship lists of 10.2% and 17.9% respectively demonstrated collaborative scholarship.

CONCLUSIONS

Despite considerable involvement from both humanities and medical practitioners, there is still substantial scope for enhanced emphasis on collaborative (multi-, inter- and trans-disciplinary) seminars and exchanges in the medical humanities and editorial policies to promote transparency of the nature of collaborative work among disciplines. Journal editors and editorial boards should reflect on the opportunity to promote enhanced visibility of joint work in scholarship in the medical humanities through reflection and review of current editorial policies.

Investigating the division of scientific labor using the Contributor Roles Taxonomy (CRediT)

Contributorship statements were introduced by scholarly journals in the late 1990s to provide more details on the specific contributions made by authors to research papers. After more than a decade of idiosyncratic taxonomies by journals, a partnership between medical journals and standards organizations has led to the establishment, in 2015, of the Contributor Roles Taxonomy (CRediT), which provides a standardized set of 14 research contributions. Using the data from Public Library of Science (PLOS) journals over the 2017–2018 period (N = 30,054 papers), this paper analyzes how research contributions are divided across research teams, focusing on the association between division of labor and number of authors, and authors’ position and specific contributions. It also assesses whether some contributions are more likely to be performed in conjunction with others and examines how the new taxonomy provides greater insight into the gendered nature of labor division. The paper concludes with a discussion of results with respect to current issues in research evaluation, science policy, and responsible research practices.

Funding acknowledgements in scientific publications: A literature review

The topic of acknowledgements has produced abundant research since the 1970s, though, as previous studies point out, the value of acknowledgements has not yet been demonstrated and further research is limited by lack of conceptualization. This study focuses on funding acknowledgements (FAs), considering that funding represents an important input in the scientific process. In this context, 183 scientific publications retrieved from Scopus from the 1970s until June 2020 were analyzed, with the aim of systematizing conceptually this body of research and contributing to a theory of acknowledgements. Results are summarized into the following main themes: the meaning of FAs; data sources for acknowledgements; the process of funding; association of funding with productivity, impact, and collaboration; and other aspects affected by funding. The literature reviewed shows that a theory of acknowledgements based on the reward triangle, as in previous studies, is unable to capture the extreme complexity of the scientific activity affecting and being affected by FAs. Funding bodies appear as clear and influential actors in the scientific communication system, making important decisions on the research that is supported, and influencing the type of knowledge produced. Funding agencies hold a responsibility regarding the data that they may collect on their programs, as well as the normalization policies they need to develop so that funded authors can reference with less ambiguity the financial source of their projects. Finally, the need to assess the impact of research funding beyond the scientific community that is, the societal impact, is also addressed.

Who are the acknowledgees? An analysis of gender and academic status

Acknowledgements found in scholarly papers allow for credit attribution of nonauthor contributors. As such, they are associated with a different kind of recognition than authorship. While several studies have shown that social factors affect authorship and citation practices,few analyses have been performed on acknowledgements. Based on 878,250 acknowledgees mentioned in 291,167 papers published between 2015 and 2017, this study analyzes the gender and academic status of individuals named in the acknowledgements of scientific papers. Our results show that gender disparities generally found in authorship can be extended to acknowledgements, and that women are even more underrepresented in acknowledgements section than in authors’ lists. Our findings also show that women acknowledge proportionally more women than men do. Regarding academic status, our results show that acknowledgees who have already published tend to have a higher position in the academic hierarchy compared with all Web of Science (WoS) authors. Taken together, these findings suggest that acknowledgement practices might be associated with academic status and gender.

Examining influential factors for acknowledgements classification using supervised learning

Acknowledgements have been examined as important elements in measuring the contributions to and intellectual debts of a scientific publication. Unlike previous studies that were limited in the scope of analysis and manual examination. The present study aimed to conduct the automatic classification of acknowledgements on a large scale of data. To this end, we first created a training dataset for acknowledgements classification by sampling the acknowledgements sections from the entire PubMed Central database. Second, we adopted various supervised learning algorithms to examine which algorithm performed best in what condition. In addition, we observed the factors affecting classification performance. We investigated the effects of the following three main aspects: classification algorithms, categories, and text representations. The CNN+Doc2Vec algorithm achieved the highest performance of 93.58% accuracy in the original dataset and 87.93% in the converted dataset. The experimental results indicated that the characteristics of categories and sentence patterns influenced the performance of classification. Most of the classifiers performed better on the categories of financial, peer interactive communication, and technical support compared to other classes.

Autoria em produções científicas: conceitos, critérios, integridade na pesquisa e responsabilidade na colaboração

Este artículo tiene el objetivo de discutir la autoría científica y los conceptos y criterios relacionados con la responsabilidad de los autores respecto de sus contribuciones; además de pretender vislumbrar los aspectos éticos y de integridad que se suscitan en la investigación y la comunicación científica. Una revisión de la literatura sobre el tema se hizo con la finalidad de buscar y obtener referencias. Los materiales seleccionados obedecieron al criterio principal de averiguar la procedencia de las fuentes científicas, tales como los libros y artículos científicos, además de algunos otros sitios de entidades oficiales que establecen normas y criterios para establecer la atribución de la autoría. Los resultados demuestran que los conceptos de autor, autoría, coautor y colaborador todavía no poseen una definición única y que englobe todo el conjunto de los criterios que constituyen la autoría. Se concluye que los investigadores pueden crear un conjunto de directrices para definir sus contribuciones y tareas, y todavía optar por la adopción de modelos o políticas de autoría sugeridos por su área, institución o por los periódicos científicos a fin de evitar los problemas relacionados con la escritura colaborativa y los artículos de autoría múltiple.

Skill ranking of researchers via hypergraph

Researchers use various skills in their works, such as writing, data analysis and experiments design. These research skills have greatly influenced the quality of their research outputs, as well as their scientific impact. Although many indicators have been proposed to quantify the impact of researchers, studies of evaluating their scientific research skills are very rare. In this paper, we analyze the factors affecting researchers' skill ranking and propose a new model based on hypergraph theory to evaluate the scientific research skills. To validate our skill ranking model, we perform experiments on the PLOS ONE dataset and compare the rank of researchers' skills with their papers' citation counts and h-index. Finally, we analyze the patterns about how researchers' skill ranking increased over time. Our studies also show the change patterns of researchers between different skills.

Factors Influencing Cities’ Publishing Efficiency

Purpose

Recently, a vast number of scientific publications have been produced in cities in emerging countries. It has long been observed that the publication output of Beijing has exceeded that of any other city in the world, including such leading centres of science as Boston, New York, London, Paris, and Tokyo. Researchers have suggested that, instead of focusing on cities’ total publication output, the quality of the output in terms of the number of highly cited papers should be examined. However, in the period from 2014 to 2016, Beijing produced as many highly cited papers as Boston, London, or New York. In this paper, another method is proposed to measure cities’ publishing performance by focusing on cities’ publishing efficiency (i.e., the ratio of highly cited articles to all articles produced in that city).

Design/methodology/approach

First, 554 cities are ranked based on their publishing efficiency, then some general factors influencing cities’ publishing efficiency are revealed. The general factors examined in this paper are as follows: the linguistic environment of cities, cities’ economic development level, the location of excellent organisations, cities’ international collaboration patterns, and their scientific field profile. Furthermore, the paper examines the fundamental differences between the general factors influencing the publishing efficiency of the top 100 most efficient cities and the bottom 100 least efficient cities.

Findings

Based on the research results, the conclusion can be drawn that a city’s publishing efficiency will be high if meets the following general conditions: it is in a country in the Anglosphere–Core; it is in a high-income country; it is home to top-ranked universities and/or world-renowned research institutions; researchers affiliated with that city most intensely collaborate with researchers affiliated with cities in the United States, Germany, England, France, Canada, Australia, and Italy; and the most productive scientific disciplines of highly cited articles are published in high-impact multidisciplinary journals, disciplines in health sciences (especially general internal medicine and oncology), and disciplines in natural sciences (especially physics, astronomy, and astrophysics).

Research limitations

It is always problematic to demarcate the boundaries of cities (e.g., New York City vs. Greater New York), and regarding this issue there is no consensus among researchers. The Web of Science presents the name of cities in the addresses reported by the authors of publications. In this paper cities correspond to the spatial units between the country/state level and the institution level as indicated in the Web of Science. Furthermore, it is necessary to highlight that the Web of Science is biased towards English-language journals and journals published in the field of biomedicine. These facts may influence the outcome of the research.

Practical implications

Publishing efficiency, as an indicator, shows how successful a city is at the production of science. Naturally, cities have limited opportunities to compete for components of the science establishment (e.g., universities, hospitals). However, cities can compete to attract innovation-oriented companies, high tech firms, and R&D facilities of multinational companies by for example establishing science parks. The positive effect of this process on the city’s performance in science can be observed in the example of Beijing, which publishing efficiency has been increased rapidly.

Originality/value

Previous scientometric studies have examined cities’ publication output in terms of the number of papers, or the number of highly cited papers, which are largely size dependent indicators; however this paper attempts to present a more quality-based approach.

All for one or one for all? Authorship and the cross-sectoral valuation of credit in nutrition science

The passionate pursuit of authorships is fuelled by the value they represent to scholars and scientists. This article asks how this value differs across scientists and how these different processes of valuation inform authorship articulation, strategies, and publication behavior in general. Drawing from a qualitative analysis of authorship practices among nutrition scientists employed at universities, contract research organizations, and in food industry, I argue that two different modi operandi emerge when it comes to authorship. These different ways of working produce different collaborative approaches, different credit distribution strategies amongst collaborators, and different value placed upon (the pursuit of) authorship. These different valuation processes are neither explicit nor recognizable to those reading (and judging) author lists. As a consequence, in the politics of authorship, the names standing atop a scientific publication in nutrition science represent different types of value to both the individuals and employing organizations.

Beyond funding: Acknowledgement patterns in biomedical, natural and social sciences

For the past 50 years, acknowledgments have been studied as important paratextual traces of research practices, collaboration, and infrastructure in science. Since 2008, funding acknowledgments have been indexed by Web of Science, supporting large-scale analyses of research funding. Applying advanced linguistic methods as well as Correspondence Analysis to more than one million acknowledgments from research articles and reviews published in 2015, this paper aims to go beyond funding disclosure and study the main types of contributions found in acknowledgments on a large scale and through disciplinary comparisons. Our analysis shows that technical support is more frequently acknowledged by scholars in Chemistry, Physics and Engineering. Earth and Space, Professional Fields, and Social Sciences are more likely to acknowledge contributions from colleagues, editors, and reviewers, while Biology acknowledgments put more emphasis on logistics and fieldwork-related tasks. Conflicts of interest disclosures (or lack of thereof) are more frequently found in acknowledgments from Clinical Medicine, Health and, to a lesser extent, Psychology. These results demonstrate that acknowledgment practices truly do vary across disciplines and that this can lead to important further research beyond the sole interest in funding.

Making visible the invisible through the analysis of acknowledgements in the humanities

Purpose

Science is subject to a normative structure that includes how the contributions and interactions between scientists are rewarded. Authorship and citations have been the key elements within the reward system of science, whereas acknowledgements, despite being a well-established element in scholarly communication, have not received the same attention. The purpose of this paper is to put forward the bearing of acknowledgements in the humanities to bring to the foreground contributions and interactions that, otherwise, would remain invisible through traditional indicators of research performance.

Design/methodology/approach

The study provides a comprehensive framework to understanding acknowledgements as part of the reward system with a special focus on their value in the humanities as a reflection of intellectual indebtedness. The distinctive features of research in the humanities are outlined and the role of acknowledgements as a source of contributorship information is reviewed to support these assumptions.

Findings

“Peer interactive communication” is the prevailing support thanked in the acknowledgements of humanities, so the notion of acknowledgements as “super-citations” can make special sense in this area. Since single-authored papers still predominate as publishing pattern in this domain, the study of acknowledgements might help to understand social interactions and intellectual influences that lie behind a piece of research and are not visible through authorship.

Originality/value

Previous works have proposed and explored the prevailing acknowledgement types by domain. This paper focusses on the humanities to show the role of acknowledgements within the reward system and highlight publication patterns and inherent research features which make acknowledgements particularly interesting in the area as a reflection of the socio-cognitive structure of research.

The many hands of science

Purpose

The purpose of this paper is to identify the research contributions of authors and subauthors in order to outline how authorship, as opposed to acknowledgment, is awarded in the lab-based life sciences.

Design/methodology/approach

The work tasks described in author contribution statements and acknowledgments sections of research articles published in Nature Chemical Biology were classified according to a three-layered taxonomy: core layer; middle layer; outer layer.

Findings

Most authors are core or middle layer contributors, i.e. they perform at least one core or middle layer task. In contrast, most subauthors are outer layer contributors. While authors tend to be involved in several tasks, subauthors tend to make single contributions. The small but significant share of authors performing only outer layer tasks suggests a disconnect in author attribution between traditional author guidelines and scientific practice. A level of arbitrariness in whether a contributor is awarded authorship or subauthorship status is reported. However, this does not implicate first or last authorships.

Research limitations/implications

Data from one journal only are used. Transferability is limited to research in high impact journals in the lab-based life sciences.

Originality/value

The growth in scientific collaboration underlines the importance of gaining a deeper understanding of the distinction between authorship and subauthorship in terms of the types of research contributions that they de facto represent. By utilizing hitherto unexplored data sources this study addresses a gap in the literature, and gives an important insight into the reward system of science.