Collaboration enhances career progression in academic science, especially for female researchers.

Collaboration and diversity are increasingly promoted in science. Yet how collaborations influence academic career progression, and whether this differs by gender, remains largely unknown. Here, we use co-authorship ego networks to quantify collaboration behaviour and career progression of a cohort of contributors to biennial International Society of Behavioral Ecology meetings (1992, 1994, 1996). Among this cohort, women were slower and less likely to become a principal investigator (PI; approximated by having at least three last-author publications) and published fewer papers over fewer years (i.e. had shorter academic careers) than men. After adjusting for publication number, women also had fewer collaborators (lower adjusted network size) and published fewer times with each co-author (lower adjusted tie strength), albeit more often with the same group of collaborators (higher adjusted clustering coefficient). Authors with stronger networks were more likely to become a PI, and those with less clustered networks did so more quickly. Women, however, showed a stronger positive relationship with adjusted network size (increased career length) and adjusted tie strength (increased likelihood to become a PI). Finally, early-career network characteristics correlated with career length. Our results suggest that large and varied collaboration networks are positively correlated with career progression, especially for women.

Analysing Time-Stamped Co-Editing Networks in Software Development Teams using git2net.

Data from software repositories have become an important foundation for the empirical study of software engineering processes. A recurring theme in the repository mining literature is the inference of developer networks capturing e.g. collaboration, coordination, or communication from the commit history of projects. Many works in this area studied networks of co-authorship of software artefacts, neglecting detailed information on code changes and code ownership available in software repositories. To address this issue, we introduce git2net, a scalable python software that facilitates the extraction of fine-grained co-editing networks in large git repositories. It uses text mining techniques to analyse the detailed history of textual modifications within files. We apply our tool in two case studies using GitHub repositories of multiple Open Source as well as a proprietary software project. Specifically, we use data on more than 1.2 million commits and more than 25,000 developers to test a hypothesis on the relation between developer productivity and co-editing patterns in software teams. We argue that git2net opens up an important new source of high-resolution data on human collaboration patterns that can be used to advance theory in empirical software engineering, computational social science, and organisational studies. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at (10.1007/s10664-020-09928-2).

Disparate foundations of scientists' policy positions on contentious biomedical research.

What drives scientists' position taking on matters where empirical answers are unavailable or contradictory? We examined the contentious debate on whether to limit experiments involving the creation of potentially pandemic pathogens. Hundreds of scientists, including Nobel laureates, have signed petitions on the debate, providing unique insights into how scientists take a public stand on important scientific policies. Using 19,257 papers published by participants, we reconstructed their collaboration networks and research specializations. Although we found significant peer associations overall, those opposing "gain-of-function" research are more sensitive to peers than are proponents. Conversely, specializing in fields directly related to gain-of-function research (immunology, virology) predicts public support better than specializing in fields related to potential pathogenic risks (such as public health) predicts opposition. These findings suggest that different social processes might drive support compared with opposition. Supporters are embedded in a tight-knit scholarly community that is likely both more familiar with and trusting of the relevant risk mitigation practices. Opponents, on the other hand, are embedded in a looser federation of widely varying academic specializations with cognate knowledge of disease and epidemics that seems to draw more heavily on peers. Understanding how scientists' social embeddedness shapes the policy actions they take is important for helping sides interpret each other's position accurately, avoiding echo-chamber effects, and protecting the role of scientific expertise in social policy.

Anatomy of funded research in science.

Seeking research funding is an essential part of academic life. Funded projects are primarily collaborative in nature through internal and external partnerships, but what role does funding play in the formulation of these partnerships? Here, by examining over 43,000 scientific projects funded over the past three decades by one of the major government research agencies in the world, we characterize how the funding landscape has changed and its impacts on the underlying collaboration networks across different scales. We observed rising inequality in the distribution of funding and that its effect was most noticeable at the institutional level--the leading universities diversified their collaborations and increasingly became the knowledge brokers in the collaboration network. Furthermore, it emerged that these leading universities formed a rich club (i.e., a cohesive core through their close ties) and this reliance among them seemed to be a determining factor for their research success, with the elites in the core overattracting resources but also rewarding in terms of both research breadth and depth. Our results reveal how collaboration networks organize in response to external driving forces, which can have major ramifications on future research strategy and government policy.

China's landscape in oncology drug research: perspectives from research collaboration networks.

OBJECTIVE: Better understanding of China's landscape in oncology drug research is of great significance for discovering anti-cancer drugs in future. This article differs from previous studies by focusing on Chinese oncology drug research communities in co-publication networks at the institutional level. Moreover, this research aims to explore structures and behaviors of relevant research units by thematic community analysis and to address policy recommendations. METHODS: This research used social network analysis to define an institutions network and to identify a community network which is characterized by thematic content. RESULTS: A total of 675 sample articles from 2008 through 2012 were retrieved from the Science Citation Index Expanded (SCIE) database of Web of Science, and top institutions and institutional pairs are highlighted for further discussion. Meanwhile, this study revealed that institutions based in the Chinese mainland are located in a relatively central position, Taiwan's institutions are closely assembled on the side, and Hong Kong's units located in the middle of the Chinese mainland's and Taiwan's. Spatial division and institutional hierarchy are still critical barriers to research collaboration in the field of anti-cancer drugs in China. In addition, the communities focusing on hot research areas show the higher nodal degree, whereas communities giving more attention to rare research subjects are relatively marginalized to the periphery of network. CONCLUSIONS: This paper offers policy recommendations to accelerate cross-regional cooperation, such as through developing information technology and increasing investment. The brokers should focus more on outreach to other institutions. Finally, participation in topics of common interest is conducive to improved efficiency in research and development (R&D) resource allocation.

The role of trophic, mutualistic, and competitive interactions in an industrial symbiosis process implementation: an ecological network perspective.

For both government and private institutions, the development of collaboration networks becomes an element of great importance for the implementation of related policies such as the circular economy and sustainable practices in manufacturing. Despite the above, such initiatives have not received as much attention in literature but have been decisive as both public and private initiatives. Initiatives in Latin America do not escape this scenario, especially in the creation of conditions that allow the promotion of approaches such as industrial symbiosis. In this way, the present research is aimed at identifying the role of trophic, mutualistic, and competitive interactions in an industrial symbiosis process implementation. A network analysis model is used to achieve this purpose. This technique allows us to know the degree of importance of the different actors that are part of a network, as well as the factors that determine the implementation of initiatives such as industrial symbiosis. Among the results are that empirical findings confirm the presence of trophic interactions that enhance resource efficiency, mutualistic interactions fostering collaboration and synergy, and competitive interactions promoting efficiency and dynamism. Additionally, a green culture, business size, and innovation activities are revealed as influential factors amplifying network dynamics.

Who counts when health counts? A case-study of multi-stakeholder initiative to promote value-creation in Swedish healthcare.

A European initiative to design a "medical information framework" conceptualised how multiple stakeholders join in collaborative networks to create innovations. It conveyed the ways in which value is created and captured by stakeholders. We applied those insights to analyse a multi-stakeholder initiative to promote improvement of Swedish healthcare. Our longitudinal case study covered totally fifty stakeholders involved in a national project, aiming at designing a system to support value-based evaluation and reimbursement. During the project the focus changed from reimbursement to benchmarking. Sophisticated case-mix adjusting algorithms were designed to make outcome comparisons valid and incorporated in a software platform enabling detailed analysis of eight patient groups across seven regional health authorities. Those were deliverables demonstrating value created. However, the project was unable to transfer the system into routine use in the regions, a failed value-capture. The initial success was promoted by collaborative processes in diagnosis-specific working groups of well-informed and engaged professionals. The change of focus away from reimbursement decreased the involvement among health authorities, leaving no centrally placed persons to push for implementation. It highlights the importance of health professionals as the key stakeholder, who has both the know-how instrumental to creating an innovation, and the local involvement guaranteeing its implementation.

Nanomedicine drug delivery in South Africa: a retrospective study on research, funding and collaboration.

After nearly two decades of substantial investment in the field of nanomedicine within South Africa, this study undertakes an investigation into the specific diseases that have been targeted for research and development, as well as the key actors and collaborative networks involved in this burgeoning field. To accomplish this, the study adopts a mixed-method approach, combining bibliometric and scientometric techniques alongside a comprehensive review of existing literature. The study's findings illuminate that the diseases selected for emphasis in nanomedicine research closely align with the prevalent health challenges faced by South Africa. Notably, these ailments encompass cancer, bacterial infections, and tuberculosis, all of which significantly contribute to the country's disease burden. Furthermore, the investigation highlights that research-intensive South African universities play a pivotal role as the primary actors in advancing nanomedicine initiatives. Over time, collaborative endeavors among these key actors have seen a noteworthy upswing. These collaborations have fostered robust connections between South African institutions and counterparts in Asian nations and the Middle East. It is worth emphasizing that nanomedicine is a resource-intensive field, necessitating substantial capital investment. Collaborative initiatives have, in turn, granted access to critical infrastructure and materials that would have otherwise been beyond the reach of some participating entities. Remarkably, these collaborative partnerships have not only facilitated scientific progress but have also cultivated social capital and trust among involved stakeholders. These valuable intangible assets hold great potential as South Africa advances towards more exploitative phases of technology development within the domain of nanomedicine. Moreover, South Africa is strategically positioning itself to cultivate a critical mass of expertise in nanomedicine, recognising the significance of skilled human resources in harnessing the full potential of this technology in the future. Systematic Review Registration: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6173875/.

Project portfolio risk management. Bibliometry and collaboration Scientometric domain analysis.

Purpose: ''Project Portfolio Risk Management" is approached through a bibliometry and collaboration networks study determining its dynamics and development as a formal domain that links Project, Risk Management and Portfolio concepts. Design/methodology/approach: To facilitate replicability, a scientometric study under a PRISMA structure is carried out: i) Identification or domain structuring, as well as keywording accuracy; ii) Screening: Search string refinement and outputs review; iii) Eligibility: Several criteria applied to a content analysis, and iv) Inclusion: Consolidation of domain analytics through bibliometry and collaboration networks. Originality and findings: Assessing the field as a formal knowledge domain is novel, contributing to a synthesis of its trends and evolution: For first time, descriptive statistics show increasing attention based on the growing citation scores, participation, H index and productivity of its main journals. Project Portfolio Selection is established as hot topic, the main authors are identified, as well as key concepts such as optimization, mathematical programming, multi-objective optimization, stochastic programming, and robust optimization. Three main research themes are obtained: Incorporation of Risk Assessment into Project Portfolio Selection problem, Risk Management as a Project Portfolio Management process, and Risk Analysis considering social and environmental issues. An accurate match is found in the contrast of the domain's behavior with some bibliometric and linguistic laws. Practical implications: Theoretical richness is achieved in the conjunction of the three terms, presenting dynamics and tendencies and thus contributing to focus related research processes on a unified field for the use of both scholars' and practitioners' perspectives.

The structural shift and collaboration capacity in GenBank Networks: A longitudinal study.

Metadata in scientific data repositories such as GenBank contain links between data submissions and related publications. As a new data source for studying collaboration networks, metadata in data repositories compensate for the limitations of publication-based research on collaboration networks. This paper reports the findings from a GenBank metadata analytics project. We used network science methods to uncover the structures and dynamics of GenBank collaboration networks from 1992-2018. The longitudinality and large scale of this data collection allowed us to unravel the evolution history of collaboration networks and identify the trend of flattening network structures over time and optimal assortative mixing range for enhancing collaboration capacity. By incorporating metadata from the data production stage with the publication stage, we uncovered new characteristics of collaboration networks as well as developed new metrics for assessing the effectiveness of enablers of collaboration-scientific and technical human capital, cyberinfrastructure, and science policy.

Collaboration Networks and Career Trajectories: What Do Metadata from Data Repositories Tell Us?

Science is increasingly carried out through scientific collaborations, allowing researchers pool their experience, knowledge, and skills. In this work we identify factors related to a scientist's collaboration capacity, their ability accumulate new collaborations over their career. To do this offer a new collaboration capacity framework and begin the work of validating it empirically by testing a number of hypotheses. We use data from GenBank, a cyberinfrastructure (CI)-enabled data repository that stores and manages scientific data. The data allow us to construct longitudinal networks, thereby giving us yearly scientific collaboration maps. We find that a scientist's network position at an early stage is related to their capacity to build new collaborations and that researchers who manage an upward trend in productivity tend to have higher collaboration capacity. Our work makes a contribution to science of science studies by offering a collaboration capacity framework and providing partial empirical support for it.

Differences in scientific collaboration and their effects on research influence: A quantitative analysis of nursing publications in Latin America (Scopus, 2005-2020).

This work is mainly aimed at the detection, visualization and description of the scientific collaboration patterns in the Nursing field in Latin America as a response to the lack of evidence on the implications of collaboration and its effects on the scientific influence in the Nursing field. For this purpose, a retrospective quantitative analysis was conducted by including all the publications classified under the code 2900 in All Science Journal Classification Codes of Scopus, corresponding to the field of General Nursing during 2005-2020. A total of 40 countries and 362,354 unique publications were analyzed, although the main subset herein consists of 18,371 unique publications authored by Latin-American institutions. World proportion of Latin-American publications in Nursing is higher than all the publications in the region. This increase is especially remarkable in the latest year of the studied period, which may result from the progressive increase in the numbers of nursing schools, the diversity in the graduate and specialization programs, the creation of scientific societies, and the many conferences carried out recently on Nursing.

A machine learning approach to quantify gender bias in collaboration practices of mathematicians.

Collaboration practices have been shown to be crucial determinants of scientific careers. We examine the effect of gender on coauthorship-based collaboration in mathematics, a discipline in which women continue to be underrepresented, especially in higher academic positions. We focus on two key aspects of scientific collaboration-the number of different coauthors and the number of single authorships. A higher number of coauthors has a positive effect on, e.g., the number of citations and productivity, while single authorships, for example, serve as evidence of scientific maturity and help to send a clear signal of one's proficiency to the community. Using machine learning-based methods, we show that collaboration networks of female mathematicians are slightly larger than those of their male colleagues when potential confounders such as seniority or total number of publications are controlled, while they author significantly fewer papers on their own. This confirms previous descriptive explorations and provides more precise models for the role of gender in collaboration in mathematics.

Trend in Spanish cardiology research and global comparative analysis of major topics.

INTRODUCTION AND OBJECTIVES: We used bibliometric techniques to analyze the participation of Spanish institutions in research on major cardiovascular topics during the last 4 decades. METHODS: Bibliometric indicators of production, collaboration and impact were obtained from the Science Citation Index Expanded (SCIE) database. Search strategies were used in major topics and institutional collaboration networks were identified, represented using the Kamada-Kawai algorithm. RESULTS: Global cardiovascular publications doubled from 2000 to 2018. In 2018, those by Spanish authors represented 2.33%, with a participation of between 7% and 1.84%, depending on the topics analyzed. The offset with respect to global production was between 0 and 7 years. Annual growth rates were higher in more recent topics. Revista Española de Cardiología published the largest number of articles from Spanish institutions. The journals generating the highest number of citations in the chosen topics were the Journal of the American College of Cardiology, Europace, and the European Heart Journal. Analysis of collaboration revealed a close interrelation between Spanish and foreign institutions, as well as groups with high production publishing independently. CONCLUSIONS: The analysis disaggregated by subject showed the sustained growth of Spanish cardiovascular scientific production and more rapid growth in recently appearing topics. Collaboration networks showed a high degree of interrelation between Spanish and foreign institutions, including hospitals, universities, research institutes, and scientific societies.

How do new members affect the relationship between principal investigator's network position and academic output of granted funds?

The paper focuses on how to improve academic output of a granted fund when the adding of new members changes principal investigator's network position. This objective is refined by exploring how new members affect the relationship between principal investigator's network position and the academic output of granted funds, and whether this effect is similar in high-output and low-output collaboration networks. New members are divided into two groups, namely, international collaboration and inbound mobility. Using negative binomial regression on research funds supported by the National Natural Science Foundation of China, the results indicate that new members indeed have moderating effects on the relationship between principal investigator's network position and the academic output of granted funds. Moreover, we find that this moderating effect in high-output collaboration networks is larger than that in low-output collaboration networks. Our findings provide practical implications for the decision makers to design funding planning and for the principal investigators to improve academic output.

What Drives the Performance of Collaboration Networks: A Qualitative Comparative Analysis of Local Water Governance in China.

Local water governance is challenging given the significance to public health and the difficulties to manage it in a fragmented administrative system. A collaboration network is a popular governance tool in local governance to cope with functional fragmentation problems and institutional collective action (ICA) dilemmas. Empirical works are needed to examine the outcomes of such governance networks, especially in the context of environmental governance. With fuzzy-set qualitative comparative analysis (fsQCA), this article seeks to evaluate the outcomes of collaboration networks by investigating the influence of network structures on local water governance performance in China. Based on empirical analyses on a dataset of twenty local water governance networks implementing the Water Ecological Civilization Pilot Project in China, the findings suggest that a high overall bridging and bonding of social capital and a low network density are important determinants of effective collaboration networks. This study has policy implications for the design of local collaboration networks in facilitating effective environmental governance.

Data to knowledge in action: A longitudinal analysis of GenBank metadata.

Studies typically use publication-based authorship data to study the relationships between collaboration networks and knowledge diffusion. However, collaboration in research often starts long before publication with data production efforts. In this project we ask how collaboration in data production networks affects and contributes to knowledge diffusion, as represented by patents, another form of knowledge diffusion. We drew our data from the metadata associated with genetic sequence records stored in the National Institutes of Health's GenBank database. After constructing networks for each year and aggregating summary statistics, regressions were used to test several hypotheses. Key among our findings is that data production team size is positively related to the number of patents each year. Also, when actors on average have more links, we tend to see more patents. Our study contributes in the area of science of science by highlighting the important role of data production in the diffusion of knowledge as measured by patents.

Bowling Together: Scientific Collaboration Networks of Demographers at European Population Conferences.

Studies of collaborative networks of demographers are relatively scarce. Similar studies in other social sciences provide insight into scholarly trends of both the fields and characteristics of their successful scientists. Exploiting a unique database of metadata for papers presented at six European Population Conferences, this report explores factors explaining research collaboration among demographers. We find that (1) collaboration among demographers has increased over the past 10 years, however, among co-authored papers, collaboration across institutions remains relatively unchanged over the period, (2) papers based on core demographic subfields such as fertility, mortality, migration and data and methods are more likely to involve multiple authors and (3) multiple author teams that are all female are less likely to co-author with colleagues in different institutions. Potential explanations for these results are discussed alongside comparisons with similar studies of collaboration networks in other related social sciences.

Social Media and Scholarly Publication: What Is the Connection?

A recent post on The Scholarly Kitchen website got me thinking about the role of social media in my professional life. I have young adult children who keep me in the loop about social trends to some extent. They instructed me to join Facebook many years ago and, since then, I have remembered friends' and relatives' birthdays with much greater success. I joined Twitter and, for a time, had a personal as well as professional account. It was difficult to keep those separate, and I eventually stopped tweeting on the personal account. I only use my professional one now and with greater circumspect (no politics and fewer complaints about hotels and airlines). I have an Instagram account where I follow many chefs, winemakers, and artists, and I enjoy the beautiful images that they post.

Centralized scientific communities are less likely to generate replicable results.

Concerns have been expressed about the robustness of experimental findings in several areas of science, but these matters have not been evaluated at scale. Here we identify a large sample of published drug-gene interaction claims curated in the Comparative Toxicogenomics Database (for example, benzo(a)pyrene decreases expression of SLC22A3) and evaluate these claims by connecting them with high-throughput experiments from the LINCS L1000 program. Our sample included 60,159 supporting findings and 4253 opposing findings about 51,292 drug-gene interaction claims in 3363 scientific articles. We show that claims reported in a single paper replicate 19.0% (95% confidence interval [CI], 16.9-21.2%) more frequently than expected, while claims reported in multiple papers replicate 45.5% (95% CI, 21.8-74.2%) more frequently than expected. We also analyze the subsample of interactions with two or more published findings (2493 claims; 6272 supporting findings; 339 opposing findings; 1282 research articles), and show that centralized scientific communities, which use similar methods and involve shared authors who contribute to many articles, propagate less replicable claims than decentralized communities, which use more diverse methods and contain more independent teams. Our findings suggest how policies that foster decentralized collaboration will increase the robustness of scientific findings in biomedical research.