Network effects on scientific collaborations

Bibliometric analysis of research trends and topic areas in traditional Chinese medicine therapy for lymphoma

CONTEXT

Traditional Chinese Medicine (TCM) is effective as a cancer treatment modality. However, this is the first bibliometric analysis of TCM in lymphoma treatment.

OBJECTIVE

This study explores the current trends and research topics of TCM in treating lymphoma from 2000 to 2023.

MATERIALS AND METHODS

We searched within the Web of Science Core Collection (WoSCC) for publications on TCM in lymphoma treatment, spanning 2000 to 2023. Subsequently, we employed a comprehensive approach utilizing CiteSpace software and VOSviewer to visually analyze research trends, authors, institutions, co-cited references, and keywords.

RESULTS

From January 1, 2000, to August 31, 2023, annual scientific publications on TCM for lymphoma treatment have steadily increased. Among the leading institutions in this field, the Beijing University of Chinese Medicine and the Fujian Medical University occupied the top positions. Regarding the authors, Jun Peng, Jiumao Lin, and Hongwei Chen emerged as the top three contributors. In the co-citation analysis of references, the top three co-cited references were authored by Hanahan D, Elmore S, and Livak KJ with citations numbered 13, 14, and 17, respectively. In particular, keywords reflecting current emerging trends included 'pathway', 'traditional Chinese medicine', 'oxidative stress', and 'macrophage polarization'.

DISCUSSION AND CONCLUSIONS

This bibliometric analysis provides a comprehensive overview of TCM for lymphoma treatment. This analysis identified the predominant trends and research topics in the field. The findings are expected to be of significant value for researchers who focus on TCM in lymphoma treatment, helping them better understand the development of this field.

Personality and emotional intelligence of researchers: The importance of affects

Researchers, who play a crucial role in knowledge production, deal with various emotions in their challenging work environment. Their personality might affect how well they manage their emotions, but their moods could help counteract these effects. This study aims to investigate whether researchers' moods influence the connection between their personality and emotional intelligence. 7,463 Spanish researchers replied to an online survey. Responses analysed through partial least squares structural equation modelling show significant positive relationships between the big five personality traits (openness to experience, conscientiousness, extraversion, agreeableness and emotional stability) and emotional intelligence. In addition, positive affect positively mediates the relationships between each of the personality traits and emotional intelligence, and negative affect mediates the same relationships but negatively. The importance of managing emotional states to regulate emotional experiences in the work of researchers is discussed.

Nonrandom behavior in the projection of random bipartite networks

There are two main categories of networks studied in the complexity physics community: Monopartite and bipartite networks. In this paper, we present a general framework that provides insights into the connection between these two classes. When a random bipartite network is projected into a monopartite network, under quite general conditions, the result is a nonrandom monopartite network, the features of which can be studied analytically. Unlike previous studies in the physics literature on complex networks, which rely on sparse-network approximations, we provide a complete analysis, focusing on the degree distribution and the clustering coefficient. Our findings primarily offer a technical contribution, adding to the current body of literature by enhancing the understanding of bipartite networks within the community of physicists. In addition, our model emphasizes the substantial difference between the information that can be extracted from a network measuring its degree distribution, or using higher-order metrics such as the clustering coefficient. We believe that our results are general and have broad real-world implications.

Bibliometric and social network analysis of a Clinical and Translational Resource awardee: An Oklahoma experience 2014-2021

Background

Social Network Analysis is a method of analyzing coauthorship networks or relationships through graph theory. Institutional Development Award (IDeA) Networks for Clinical and Translational Research (IDeA-CTR) was designed to expand the capability for clinical and translational research to enhance National Institutes of Health funding.

Methods

All publications from a cohort of clinical and translational scientists in Oklahoma were collected through a PubMed search for 2014 through 2021 in October 2022. For this study's bibliometric portion, we pulled the citations from iCite in November of 2022.

Results

There were 2,391 articles published in 1,019 journals. The number of papers published by year increased from 56 in 2014 to 448 in 2021. The network had an average of 6.4 authors per paper, with this increasing by year from 5.3 in 2014 to 6.9 in 2021. The average journal impact factor for the overall network was 7.19, with a range from 0.08 to 202.73. The Oklahoma Shared Clinical and Translational Resources (OSCTR) network is a small world network with relatively weak ties.

Conclusions

This study provides an overview of coauthorship in an IDeA-CTR collaboration. We show the growth and structure of coauthorship in OSCTR, highlighting the importance of understanding and fostering collaboration within research networks.

Exploring high scientific productivity in international co-authorship of a small developing country based on collaboration patterns

The number of published scientific paper grows rapidly each year, totaling more than 2.9 million annually. New methodologies and systems have been developed to analyze scientific production and performance indicators from large quantities of data available from the scientific databases, such as Web of Science or Scopus. In this paper, we analyzed the international scientific production and co-authorship patterns for the most productive authors from Serbia based on the obtained Web of Science dataset in the period 2006-2013. We performed bibliometric and scientometric analyses together with statistical and collaboration network analysis, to reveal the causes of extraordinary publishing performance of some authors. For such authors, we found significant inequality in distribution of papers over journals and countries of co-authors, using Gini coefficient and Lorenz curves. Most of the papers belong to multidisciplinary, interdisciplinary, and the field of applied sciences. We have discovered three specific collaboration patterns that lead to high productivity in international collaboration. First pattern corresponds to mega-authorship papers with hundreds of co-authors gathered in specific research groups. The other two collaboration patterns were found in mathematics and multidisciplinary science, mainly application of graph theory and computational methods in physical chemistry. The former pattern results in a star-shaped collaboration network with mostly individual collaborators. The latter pattern includes multiple actors with high betweenness centrality measure and identified brokerage roles. The results are compared with the later period 2014-2023, where high scientific production has been observed in some other fields, such as biology and food science and technology.

Higher-order rich-club phenomenon in collaborative research grant networks

Modern scientific work, including writing papers and submitting research grant proposals, increasingly involves researchers from different institutions. In grant collaborations, it is known that institutions involved in many collaborations tend to densely collaborate with each other, forming rich clubs. Here we investigate higher-order rich-club phenomena in networks of collaborative research grants among institutions and their associations with research impact. Using publicly available data from the National Science Foundation in the US, we construct a bipartite network of institutions and collaborative grants, which distinguishes among the collaboration with different numbers of institutions. By extending the concept and algorithms of the rich club for dyadic networks to the case of bipartite networks, we find rich clubs both in the entire bipartite network and the bipartite subnetwork induced by the collaborative grants involving a given number of institutions up to five. We also find that the collaborative grants within rich clubs tend to be more impactful in a per-dollar sense than the control. Our results highlight advantages of collaborative grants among the institutions in the rich clubs.

Women and key positions in scientific collaboration networks: analyzing central scientists’ profiles in the artificial intelligence ecosystem through a gender lens

Scientific collaboration in almost every discipline is mainly driven by the need of sharing knowledge, expertise, and pooled resources. Science is becoming more complex which has encouraged scientists to involve more in collaborative research projects in order to better address the challenges. As a highly interdisciplinary field with a rapidly evolving scientific landscape, artificial intelligence calls for researchers with special profiles covering a diverse set of skills and expertise. Understanding gender aspects of scientific collaboration is of paramount importance, especially in a field such as artificial intelligence that has been attracting large investments. Using social network analysis, natural language processing, and machine learning and focusing on artificial intelligence publications for the period from 2000 to 2019, in this work, we comprehensively investigated the effects of several driving factors on acquiring key positions in scientific collaboration networks through a gender lens. It was found that, regardless of gender, scientific performance in terms of quantity and impact plays a crucial part in possessing the “social researcher” role in the network. However, subtle differences were observed between female and male researchers in acquiring the “local influencer” role.

Current Status and Trends in Research on Caries Diagnosis: A Bibliometric Analysis

There are a wide variety of devices for the detection and diagnosis of caries from the initial stages. The purpose of this study was to perform a bibliometric study on research regarding caries diagnosis by identifying the contributing researchers, organizations, countries or regions, journals, and to provide an analysis of keyword co-occurrence and co-authorship networks. An advanced search was performed in Web of Science (WOS) Core Collection database, using the terms “caries diagno*” and “caries detect*” in the “topic” field, from 2013 to 2021. Bibliometric parameters were extracted using WOS’s analyze results tools and VOSviewer software. A total of 816 documents were identified. Most of them, (61.3%) are included in “Dentistry Oral Surgery & Medicine” category within WOS. The largest scientific production on the subject is observed between 2018 and 2021, with a total of 344 records. The most productive author is Mendes FM, followed by Braga MM. The journal with the most articles published on caries diagnosis is Caries Research, with 55 articles (6.74%). The terms with the highest co-occurrence refer to the validity of diagnostic methods, tools or principles used in diagnosis or general aspects related to caries detection and diagnosis.

A Systematic Review on Amaranthus-Related Research

Leafy vegetables promote reparation of energy loss due to oxidative stress, and they have the potential to alleviate hunger and malnutrition as well as other forms of metabolic imbalance ravaging the world. However, these vegetables are underutilized, despite the fact that they harbor essential minerals needed for critical cellular activities. As amaranth is one of the earliest vegetables reputed for its high nutraceutical and therapeutic value, in this study, we explored research on the Amaranthus species, and identified areas with knowledge gaps, to harness the various biological and economic potentials of the species. Relevant published documents on the plant were retrieved from the Science Citation Index Expanded accessed through the Web of Science from 2011 to 2020; while RStudio and VOSviewer were used for data analysis and visualization, respectively. Publications over the past decade (dominated by researchers from the USA, India, and China, with a collaboration index of 3.22) showed that Amaranthus research experienced steady growth. Findings from the study revealed the importance of the research and knowledge gaps in the underutilization of the vegetable. This could be helpful in identifying prominent researchers who can be supported by government funds, to address the malnutrition problem in developing countries throughout the world.

A large National Institute for Health Research (NIHR) Biomedical Research Centre facilitates impactful cross-disciplinary and collaborative translational research publications and research collaboration networks: a bibliometric evaluation study

Background

The evaluation of translational health research is important for various reasons such as the research impact assessment, research funding allocation, accountability, and strategic research policy formulation. The purpose of this study was to evaluate the research productivity, strength and diversity of research collaboration networks and impact of research supported by a large biomedical research centre in the United Kingdom (UK).

Methods

Bibliometric analysis of research publications by translational researchers affiliated with the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre (BRC) from April 2012 to March 2017.

Results

Analysis included 2377 translational research publications that were published during the second 5-year funding period of the NIHR Oxford BRC. Author details were available for 99.75% of the publications with DOIs (2359 of 2365 with DOIs), and the number of authors per publication was median 9 (mean  = 18.03, SD  = 3.63, maximum  = 2467 authors). Author lists also contained many consortia, groups, committees, and teams (n  = 165 in total), with 1238 additional contributors, where membership was reported. The BRC co-authorship i.e., research collaboration network for these publications involved 20,229 nodes (authors, of which 1606 nodes had Oxford affiliations), and approximately 4.3 million edges (authorship linkages). Articles with a valid DOIs (2365 of 2377, 99.5%) were collectively cited more than 155,000 times and the average Field Citation Ratio was median 6.75 (geometric mean  = 7.12) while the average Relative Citation Ratio was median 1.50 (geometric mean  = 1.83) for the analysed publications.

Conclusions

The NIHR Oxford BRC generated substantial translational research publications and facilitated a huge collaborative network of translational researchers working in complex structures and consortia, which shows success across the whole of this BRC funding period. Further research involving continued uptake of unique persistent identifiers and the tracking of other research outputs such as clinical innovations and patents would allow a more detailed understanding of large research enterprises such as NIHR BRCs in the UK.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12967-021-03149-x.

Bibliometric analysis of COVID-19 related publications in Indian orthopaedic journals

BACKGROUND

The COVID-19 pandemic has resulted in an infodemic about the novel coronavirus SARS-CoV-2 outbreak to build knowledge and develop mitigation strategies. In addition, scientific journals across the world have studied the impact of COVID-19 on trauma and orthopaedics.

METHODS

A cross-sectional, bibliometric analysis of the literature was undertaken on COVID-19 related articles from three Pubmed and Scopus indexed orthopaedic journals from India, namely, Indian Journal of Orthopaedics(IJO),Journal of Clinical Orthopaedics and Trauma(JCOT), and Journal of Orthopaedics (JOO), in May 2021. All the article types and study designs were included for this review. The authors, institutions, countries, keywords, and co-authorship mapping were studied.

RESULTS

A total of 112 COVID-19 related documents were retrieved. Period of these publications was from 2^nd April 2020 to 31^st May 2021. Vaishya R. (n = 16) was the most cited author, and Indraprastha Apollo Hospitals (n = 16) was the most cited research Institution. India led the list of countries in academic publication output. On keyword mapping, telemedicine was the most prominent Medical Subject Headings (MeSH) search word.

CONCLUSION

The Indian orthopedic journals have addressed the impact of COVID-19 on orthopaedic practice in India and aborad whilst continuing to publish knowledge about basic science and clinical orthopaedic research studies. The JCOT has outperformed and become the most leading orthopaedic journal from India during the pandemic. COVID -19 articles have been fast tracked, open accessed and attracted more citations in reduced duration of time compared to non-COVID-19 papers.

Interplay between success and patterns of human collaboration: case study of a Thai Research Institute

Networks of collaboration are notoriously complex and the mechanisms underlying their evolution, although of high interest, are still not fully understood. In particular, collaboration networks can be used to model the interactions between scientists and analyze the circumstances that lead to successful research. This task is not trivial and conventional metrics, based on number of publications and number of citations of individual authors, may not be sufficient to provide a deep insight into the factors driving scientific success. However, network analysis techniques based on centrality measures and measures of the structural properties of the network are promising to that effect. In recent years, it has become evident that most successful research works are achieved by teams rather than individual researchers. Therefore, researchers have developed a keen interest in the dynamics of social groups. In this study, we use real world data from a Thai computer technology research center, where researchers collaborate on different projects and team up to produce a range of artifacts. For each artifact, a score that measures quality of research is available and shared between the researchers that contributed to its creation, according to their percentage of contribution. We identify several measures to quantify productivity and quality of work, as well as centrality measures and structural measures. We find that, at individual level, centrality metrics are linked to high productivity and quality of work, suggesting that researchers who cover strategic positions in the network of collaboration are more successful. At the team level, we show that the evolution in time of structural measures are also linked to high productivity and quality of work. This result suggests that variables such as team size, turnover rate, team compactness and team openness are critical factors that must be taken into account for the success of a team. The key findings of this study indicate that the success of a research institute needs to be assessed in the context of not just researcher or team level, but also on how the researchers engage in collaboration as well as on how teams evolve.

Increasing collaborative research output between early-career health researchers in Africa: lessons from the CARTA fellowship program

In 2008 nine African Universities and four African research institutions, in partnership with non-African institutions started the Consortium for Advanced Research Training in Africa (CARTA) to strengthen doctoral training and research capacity on health in Africa. This study describes particular aspects of the CARTA program that promotes collaboration between the PhD fellows in the program, and determines the patterns of collaborative publications that resulted from the intervention. We reviewed program monitoring and evaluation documents and conducted a bibliometric analysis of 806 peer-reviewed publications by CARTA fellows published between 2011 and 2018. Results indicate that recruiting multidisciplinary fellows from various institutions, encouraging registration of doctoral-level fellows outside home institutions, and organizing joint research seminars stimulated collaborative research on health-related topics. Fellows collaborated among themselves and with non-CARTA researchers. Fellows co-authored 75 papers (10%) between themselves, of which 53 (71%) and 42 (56%) included fellows of different cohorts and different disciplines respectively, and 19 (25%) involved fellows of different institutions. CARTA graduates continued to publish with each other after graduating - 11% of the collaborative publications occurred post-graduation - indicating that the collaborative approach was maintained after exiting from the program. However, not all fellows contributed to publishing collaborative papers. The study recommends concerted effort towards enhancing collaborative publications among the CARTA fellows, both doctoral and post-doctoral, which can include holding research exchange forums and collaborative grant-writing workshops.

Measuring researchers' potential scholarly impact with structural variations: Four types of researchers in information science (1979-2018)

We propose a method to measure the potential scholarly impact of researchers based on network structural variations they introduced to the underlying author co-citation network of their field. We applied the method to the information science field based on 91,978 papers published between 1979 and 2018 from the Web of Science. We divided the entire period into eight consecutive intervals and measured structural variation change rates (ΔM) of individual authors in corresponding author co-citation networks. Four types of researchers are identified in terms of temporal dynamics of their potential scholarly impact—1) Increasing, 2) Decreasing, 3) Sustained, and 4) Transient. The study contributes to the understanding of how researchers’ scholarly impact might evolve in a broad context of the corresponding research community. Specifically, this study illustrated a crucial role played by structural variation metrics in measuring and explaining the potential scholarly impact of a researcher. This method based on the structural variation analysis offers a theoretical framework and a practical platform to analyze the potential scholarly impact of researchers and their specific contributions.

Author-related factors predicting citation counts of conference papers: focusing on computer and information science

Purpose

This paper aims to assess the predictive power of authorship properties determined at the time of publishing conference papers on future citations of conference papers in computer and information science.

Design/methodology/approach

This study examined 21 factors – related to all authors and to the first author – as potentially predictive of citation counts. Specifically, the study assessed properties of author's academic performance, degree of collaboration and topological properties of their research collaboration networks.

Findings

The results of comparing all authors with first authors indicate that the all author-related factors have a significantly higher power for explaining conference paper citation counts than the first author-related factors. Moreover, among the all author-related factors, the degree centrality before the target paper made the largest contribution.

Originality/value

This is one of the first attempts to focus on the relationship of author characteristics to conference papers. This is also one of only a few studies to expand prior research, which limited its bibliometric foci to journal articles, to conference papers.

The dynamics of collaboration networks and the history of general relativity, 1925–1970

This paper presents a novel methodology for defining and analyzing the dynamics of the collaboration networks of scientists working on general relativity from the mid-1920s–1970. During these four and a half decades the status of the theory underwent a radical transformation: from a marginal theory before the mid-1950s to a pillar of modern physics. To investigate this passage—known as the renaissance of general relativity—we used a definition of collaboration networks broader than the co-authorship relations retrievable from online datasets. We constructed a multilayer network, in which each layer represents a different kind of collaboration. After having analyzed the evolution over time of specific parameters of the co-authorship network, we investigated the effects of adding one type of collaboration edge at a time, in a cumulative fashion, on the values of these parameters and on the topology of the collaboration network through time, including rapid shifts in the dynamic evolution of the largest component. This analysis provides robust quantitative evidence that a shift in the structure of the relativity collaboration network occurred between the late 1950s and the early 1960s, when a giant component started forming. We interpret this shift as the central social dynamic of the renaissance process and then identify its central actors. Our analysis disproves common explanations of the renaissance process. It shows that this phenomenon was not a consequence of astrophysical discoveries in the 1960s, nor was it a simple by-product of socio-economic transformations in the physics landscape after World War II.

Research collaboration and knowledge sharing in e-governance

Purpose

This paper aims to introduce a systematic computing and analytical procedure that is applied to the co-author network to identify the temporal evolution and growth of research collaborations in the area of e-governance. The empirical analysis of the temporal co-author network can trace the emerging authors and knowledge bursts over time.

Design/methodology/approach

The study applied social network theory to trace the author collaboration patterns in the domain of e-governance. Analysis of the co-author network using micro and macro parameters was done to trace the temporal evolution of the author collaborations.

Findings

E-governance is a multi-disciplinary research domain split over streams of management, politics, information technology and electronics. Hence, research collaborations play a significant role in its advancement. The knowledge sharing between individual authors, institutions and groups through research collaborations, resulting in extensive sharing of data, equipment and research methods, has boosted research activities and development in e-governance. In this paper, the authors systematically analyse the current scenario of research collaborations in the area of e-governance using co-author network to estimate its impact on the advancement of the field. The authors also analysed the temporal evolution of the co-author networks, which show remarkable growth of research collaborations in the domain of e-governance from the year 2000.

Research limitations/implications

The co-author network analysis is only a proxy measure for the analysis of research collaborations. The names of the authors and the university affiliations used in the article are as retrieved from the research repository of Scopus. The degree, citations and other parameters related with authors have scope only within the environment of the co-author network used in the analysis. The criteria used in the study is limited to the degree of research collaborations and the number of co-authored publications in the giant component of the co-author network.

Practical implications

Institutions, authors and governments can trace and select suitable topics and choose research groups of co-authors over the world for future research collaborations in e-governance. The knowledge about the emerging and most discussed topics gives an overview of the global research trends of e-governance.

Social implications

The study identified the evolution of creative collaborations in e-governance in the global perspective. The methodology introduced here is helpful to detect the proficient and productive author collaborations and the spectrum of related e-governance research topics associated with them. As the author collaborations can be mapped to the institutional and country-level collaborations, the information is helpful for researchers, institutions and governments to establish the best collaborations in e-governance research based on the author proficiency, collaboration patterns and research topics as per the requirements.

Originality/value

The paper introduces a novel research methodology using temporal analysis of co-author network to identify the evolution of research patterns and the associated research topics.

Power Quality: Scientific Collaboration Networks and Research Trends

Power quality is a research field related to the proper operation of devices and technological equipment in industry, service, and domestic activities. The level of power quality is determined by variations in voltage, frequency, and waveforms with respect to reference values. These variations correspond to different types of disturbances, including power fluctuations, interruptions, and transients. Several studies have been focused on analysing power quality issues. However, there is a lack of studies on the analysis of both the trending topics and the scientific collaboration network underlying the field of power quality. To address these aspects, an advanced model is used to retrieve data from publications related to power quality and analyse this information using a graph visualisation software and statistical tools. The results suggest that research interests are mainly focused on the analysis of power quality problems and mitigation techniques. Furthermore, they are observed important collaboration networks between researchers within and across countries.

Network effects in environmental justice struggles: An investigation of conflicts between mining companies and civil society organizations from a network perspective

This paper examines conflicts that occur between mining companies and civil society organizations (CSOs) around the world and offers an innovative analysis of mining conflicts from a social network perspective. The analysis showed that, as the number of CSOs involved in a conflict increased, its outcome was more likely to be perceived as a success in terms of environmental justice (EJ); if a CSO was connected to other central CSOs, the average perception of EJ success was likely to increase; and as network distance between two conflicts increased (or decreased), they were more likely to lead to different (or similar) EJ outcomes. Such network effects in mining conflicts have policy implications for EJ movements. It would be a strategic move on the part of successful CSOs to become involved in other major conflicts and disseminate information about how they achieved greater EJ success.

Collaboration patterns in the German political science co-authorship network

Research on social processes in the production of scientific output suggests that the collective research agenda of a discipline is influenced by its structural features, such as "invisible colleges" or "groups of collaborators" as well as academic "stars" that are embedded in, or connect, these research groups. Based on an encompassing dataset that takes into account multiple publication types including journals and chapters in edited volumes, we analyze the complete co-authorship network of all 1,339 researchers in German political science. Through the use of consensus graph clustering techniques and descriptive centrality measures, we identify the ten largest research clusters, their research topics, and the most central researchers who act as bridges and connect these clusters. We also aggregate the findings at the level of research organizations and consider the inter-university co-authorship network. The findings indicate that German political science is structured by multiple overlapping research clusters with a dominance of the subfields of international relations, comparative politics and political sociology. A small set of well-connected universities takes leading roles in these informal research groups.

Evaluating a European knowledge hub on climate change in agriculture: Are we building a better connected community?

In order to maintain food security and sustainability of production under climate change, interdisciplinary and international collaboration in research is essential. In the EU, knowledge hubs are important funding instruments for the development of an interconnected European Research Area. Here, network analysis was used to assess whether the pilot knowledge hub MACSUR has affected interdisciplinary collaboration, using co-authorship of peer reviewed articles as a measure of collaboration. The broad community of all authors identified as active in the field of agriculture and climate change was increasingly well connected over the period studied. Between knowledge hub members, changes in network parameters suggest an increase in collaborative interaction beyond that expected due to network growth, and greater than that found in the broader community. Given that interdisciplinary networks often take several years to have an impact on research outputs, these changes within the relatively new MACSUR community provide evidence that the knowledge hub structure has been effective in stimulating collaboration. However, analysis showed that knowledge hub partners were initially well-connected, suggesting that the initiative may have gathered together researchers with particular resources or inclinations towards collaborative working. Long term, consistent funding and ongoing reflection to improve networking structures may be necessary to sustain the early positive signs from MACSUR, to extend its success to a wider community of researchers, or to repeat it in less connected fields of science. Tackling complex challenges such as climate change will require research structures that can effectively support and utilise the diversity of talents beyond the already well-connected core of scientists at major research institutes. But network research shows that this core, well-connected group are vital brokers in achieving wider integration.

Implications of Scientific Collaboration Networks on Studies of Aquatic Vertebrates in the Brazilian Amazon

The quantity of wildlife extracted from the Amazon has increased in the past decades as a consequence of an increase in human population density and income growth. To evaluate the spatial distribution of studies on subsistence and/or commercial hunting conducted in the Brazilian Amazon, we selected eight mid-sized and large-bodied aquatic vertebrate species with a history of human exploitation in the region. We used a combination of searches in the gray and scientific literature from the past 24 years to provide an updated distributional map of studies on the target species. We calculated the distances between the study sites and the locations of the research institutes/universities that the first and last authors of the same study were affiliated to. For the period of 1990 to 2014, we found 105 studies on the subsistence and/or commercial hunting of aquatic vertebrates in the Brazilian Amazon in 271 locations that involved 43 institutions (37 Brazilian and 6 international). The spatial distribution of the studies across the Brazilian Amazon varied, but over 80% took place in the northeast and central Amazon, encompassing three States of the Legal Brazilian Amazon (Amazonas, 51.42%; Pará, 19.05%; and Amapá, 16.19%). Over half of the research study sites (52.91%) were within 500 km of the research institute/university of the first or last authors. Some research institutes/universities did not have any inter-institutional collaborations, while others collaborated with eight or more institutes. Some research institutes/universities conducted many studies, had an extensive collaboration network, and contributed greatly to the network of studies on Amazonian aquatic vertebrates. Our research contributes to the knowledge of studies on the subsistence and/or commercial hunting of the most exploited aquatic vertebrates of the Brazilian Amazon, illustrates the impact that collaboration networks have on research, and highlights potential areas for improvement and the generation of new collaborations.

Perceptions of Scholars in the Field of Economics on Co-Authorship Associations: Evidence from an International Survey

Scholars (n = 580) from 69 countries who had contributed articles in the field of Economics during the year 2015 participated in a survey that gauged their perceptions of various aspects of co-authorship, including its benefits, motivations, working relationships, order of authorship and association preferences. Among the main findings, significant differences emerged in the proportion of co-authored papers based on age, gender and number of years the researchers had spent in their present institution. Female scholars had a greater proportion of co-authored papers than male scholars. Respondents considered improved quality of paper, contribution of mutual expertise, and division of labor as the biggest benefits of and motivation for co-authorship. Contrary to common perceptions that Economics researchers used a predominantly alphabetical order of authorship, our study found that a considerable percentage of respondents (34.5%) had practiced an order of authorship based on the significance of the authors' contribution to the work. The relative importance of tasks differed significantly according to whether researchers co-authored as mentors or co-authored as colleagues. Lastly, researchers were found to associate, to varying degrees, with other researchers based on socio-academic parameters, such as nationality, ethnicity, gender, professional position and friendship. The study indicates that Economics authors perceive co-authorship as a rewarding endeavor. Nonetheless, the level of contribution and even the choice of association itself as a co-author depends to a great extent on the type of working relationship and socio-academic factors.

Evolution and convergence of the patterns of international scientific collaboration

International research collaboration plays an important role in the social construction and evolution of science. Studies of science increasingly analyze international collaboration across multiple organizations for its impetus in improving research quality, advancing efficiency of the scientific production, and fostering breakthroughs in a shorter time. However, long-run patterns of international research collaboration across scientific fields and their structural changes over time are hardly known. Here we show the convergence of international scientific collaboration across research fields over time. Our study uses a dataset by the National Science Foundation and computes the fraction of papers that have international institutional coauthorships for various fields of science. We compare our results with pioneering studies carried out in the 1970s and 1990s by applying a standardization method that transforms all fractions of internationally coauthored papers into a comparable framework. We find, over 1973-2012, that the evolution of collaboration patterns across scientific disciplines seems to generate a convergence between applied and basic sciences. We also show that the general architecture of international scientific collaboration, based on the ranking of fractions of international coauthorships for different scientific fields per year, has tended to be unchanged over time, at least until now. Overall, this study shows, to our knowledge for the first time, the evolution of the patterns of international scientific collaboration starting from initial results described by literature in the 1970s and 1990s. We find a convergence of these long-run collaboration patterns between the applied and basic sciences. This convergence might be one of contributing factors that supports the evolution of modern scientific fields.

Network analysis of RE-AIM framework: chronology of the field and the connectivity of its contributors

The reach, effectiveness, adoption, implementation, and maintenance (RE-AIM) framework has been widely used for translational research. We used social network analysis (SNA) to explore how innovative research frameworks, such as RE-AIM, have diffused over time in academic literature. A structured literature review was conducted on RE-AIM between 1999 and 2012. SNA indices of degree score, betweenness, centrality, and authorship ties were used to examine use of RE-AIM. Use of RE-AIM has grown since its inception and spread from a few research centers to use internationally. Investigation of co-authorship revealed many have published on RE-AIM, but a much smaller core of RE-AIM researchers have published together two or more times. SNA revealed how the RE-AIM framework has been used over time and identified areas to further expand use of the framework. SNA can be useful to understand how research frameworks diffuse over time.

The importance of national and international collaboration in adult congenital heart disease: A network analysis of research output

BACKGROUND

The determinants of adult congenital heart disease (ACHD) research output are only partially understood. The heterogeneity of ACHD naturally calls for collaborative work; however, limited information exists on the impact of collaboration on academic performance. We aimed to examine the global topology of ACHD research, distribution of research collaboration and its association with cumulative research output.

METHODS AND RESULTS

Based on publications presenting original research between 2005 and 2011, a network analysis was performed quantifying centrality measures and key players in the field of ACHD. In addition, network maps were produced to illustrate the global distribution and interconnected nature of ACHD research. The proportion of collaborative research was 35.6 % overall, with a wide variation between countries (7.1 to 62.8%). The degree of research collaboration, as well as measures of network centrality (betweenness and degree centrality), were statistically associated with cumulative research output independently of national wealth and available workforce. The global ACHD research network was found to be scale-free with a small number of central hubs and a relatively large number of peripheral nodes. In addition, we could identify potentially influential hubs based on cluster analysis and measures of centrality/key player analysis.

CONCLUSIONS

Using network analysis methods the current study illustrates the complex and global structures of ACHD research. It suggests that collaboration between research institutions is associated with higher academic output. As a consequence national and international collaboration in ACHD research should be encouraged and the creation of an adequate supporting infrastructure should be further promoted.

A framework to explore the knowledge structure of multidisciplinary research fields

Understanding emerging areas of a multidisciplinary research field is crucial for researchers, policymakers and other stakeholders. For them a knowledge structure based on longitudinal bibliographic data can be an effective instrument. But with the vast amount of available online information it is often hard to understand the knowledge structure for data. In this paper, we present a novel approach for retrieving online bibliographic data and propose a framework for exploring knowledge structure. We also present several longitudinal analyses to interpret and visualize the last 20 years of published obesity research data.

Co-authorship networks: a review of the literature

Purpose

– The purpose of this paper is to attempt to provide a review of the growing literature on co-authorship networks and the research gaps that may be investigated for future studies in this field.

Design/methodology/approach

– The existing literature on co-authorship networks was identified, evaluated and interpreted. Narrative review style was followed.

Findings

– Co-authorship, a proxy of research collaboration, is a key mechanism that links different sets of talent to produce a research output. Co-authorship could also be seen from the perspective of social networks. An in-depth analysis of such knowledge networks provides an opportunity to investigate its structure. Patterns of these relationships could reveal, for example, the mechanism that shapes our scientific community. The study provides a review of the expanding literature on co-authorship networks.

Originality/value

– This is one of the first comprehensive reviews of network-based studies on co-authorship. The field is fast evolving, opening new gaps for potential research. The study identifies some of these gaps.

Fragmented Romanian sociology: growth and structure of the collaboration network

Structural patterns in collaboration networks are essential for understanding how new ideas, research practices, innovation or cooperation circulate and develop within academic communities and between and within university departments. In our research, we explore and investigate the structure of the collaboration network formed by the academics working full-time within all the 17 sociology departments across Romania. We show that the collaboration network is sparse and fragmented, and that it constitutes an environment that does not promote the circulation of new ideas and innovation within the field. Although recent years have witnessed an increase in the productivity of Romanian sociologists, there is still ample room for improvement in terms of the interaction infrastructure that ought to link individuals together so that they could maximize their potentials. We also fail to discern evidence in favor of the Matthew effect governing the growth of the network, which suggests scientific success and productivity are not rewarded. Instead, the structural properties of the collaboration network are partly those of a core-periphery network, where the spread of innovation and change can be explained by structural equivalence rather than by interpersonal influence models. We also provide support for the idea that, within the observed network, collaboration is the product of homophily rather than prestige effects. Further research on the subject based on data from other countries in the region is needed to place our results in a comparative framework, in particular to discern whether the behavior of the Romanian sociologist community is unique or rather common.

CollaborationViz: interactive visual exploration of biomedical research collaboration networks

Social network analysis (SNA) helps us understand patterns of interaction between social entities. A number of SNA studies have shed light on the characteristics of research collaboration networks (RCNs). Especially, in the Clinical Translational Science Award (CTSA) community, SNA provides us a set of effective tools to quantitatively assess research collaborations and the impact of CTSA. However, descriptive network statistics are difficult for non-experts to understand. In this article, we present our experiences of building meaningful network visualizations to facilitate a series of visual analysis tasks. The basis of our design is multidimensional, visual aggregation of network dynamics. The resulting visualizations can help uncover hidden structures in the networks, elicit new observations of the network dynamics, compare different investigators and investigator groups, determine critical factors to the network evolution, and help direct further analyses. We applied our visualization techniques to explore the biomedical RCNs at the University of Arkansas for Medical Sciences – a CTSA institution. And, we created CollaborationViz, an open-source visual analytical tool to help network researchers and administration apprehend the network dynamics of research collaborations through interactive visualization.

Co-authorship and bibliographic coupling network effects on citations

This paper analyzes the effects of the co-authorship and bibliographic coupling networks on the citations received by scientific articles. It expands prior research that limited its focus on the position of co-authors and incorporates the effects of the use of knowledge sources within articles: references. By creating a network on the basis of shared references, we propose a way to understand whether an article bridges among extant strands of literature and infer the size of its research community and its embeddedness. Thus, we map onto the article--our unit of analysis--the metrics of authors' position in the co-authorship network and of the use of knowledge on which the scientific article is grounded. Specifically, we adopt centrality measures--degree, betweenneess, and closeness centrality--in the co-authorship network and degree, betweenness centrality and clustering coefficient in the bibliographic coupling and show their influence on the citations received in first two years after the year of publication. Findings show that authors' degree positively impacts citations. Also closeness centrality has a positive effect manifested only when the giant component is relevant. Author's betweenness centrality has instead a negative effect that persists until the giant component--largest component of the network in which all nodes can be linked by a path--is relevant. Moreover, articles that draw on fragmented strands of literature tend to be cited more, whereas the size of the scientific research community and the embeddedness of the article in a cohesive cluster of literature have no effect.