scholarly journals Mapping the collaboration networks of biomedical research in Southeast Asia

2015 ◽  
Author(s):  
Vincent Schubert R Malbas
Keyword(s):  
Network Analysis ◽  
Southeast Asia ◽  
Biomedical Research ◽  
Research Collaboration ◽  
Research Network ◽  
Collaboration Networks ◽  
Health Issues ◽  
Group Influence ◽  
Regional Collaboration ◽  
Bibliographic Records

Collaboration forms an integral aspect of global research endeavors, where co-authorship derived from bibliographic records provides the building block for mapping research collaboration networks. Bibliometric techniques and social network analysis tools were applied to measure the scope and depth of collaboration in biomedical research in Southeast Asia during the period 2005-2009. In particular, centrality scores and draw network maps were calculated for both country and institutional levels of aggregation. In the field of biomedical research, Thailand and Singapore are the most productive and collaborative countries in Southeast Asia during the period studied. Using network analysis, there was strong correlation of research productivity by a country or institution with the number of collaboration and its group influence, and weak correlation with maximal data flow within the research network. There were specific clusters of connected institutions in subnetworks for neoplasm, diabetes, and tuberculosis research. Given the observed frequency of regional collaboration in Southeast Asia, in comparison to foreign collaboration, it is argued that increasing the number of collaborations within Southeast Asia will help advance the region’s efforts on domestic and regional health issues.

scholarly journals Mapping the collaboration networks of biomedical research in Southeast Asia

2015 ◽  
Author(s):  
Vincent Schubert R Malbas
Keyword(s):  
Network Analysis ◽  
Southeast Asia ◽  
Biomedical Research ◽  
Research Collaboration ◽  
Research Network ◽  
Collaboration Networks ◽  
Health Issues ◽  
Group Influence ◽  
Regional Collaboration ◽  
Bibliographic Records

Collaboration forms an integral aspect of global research endeavors, where co-authorship derived from bibliographic records provides the building block for mapping research collaboration networks. Bibliometric techniques and social network analysis tools were applied to measure the scope and depth of collaboration in biomedical research in Southeast Asia during the period 2005-2009. In particular, centrality scores and draw network maps were calculated for both country and institutional levels of aggregation. In the field of biomedical research, Thailand and Singapore are the most productive and collaborative countries in Southeast Asia during the period studied. Using network analysis, there was strong correlation of research productivity by a country or institution with the number of collaboration and its group influence, and weak correlation with maximal data flow within the research network. There were specific clusters of connected institutions in subnetworks for neoplasm, diabetes, and tuberculosis research. Given the observed frequency of regional collaboration in Southeast Asia, in comparison to foreign collaboration, it is argued that increasing the number of collaborations within Southeast Asia will help advance the region’s efforts on domestic and regional health issues.

scholarly journals Social network analysis of biomedical research collaboration networks in a CTSA institution

2014 ◽  
Vol 52 ◽  
pp. 130-140 ◽  
Author(s):  
Jiang Bian ◽  
Mengjun Xie ◽  
Umit Topaloglu ◽  
Teresa Hudson ◽  
Hari Eswaran ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Biomedical Research ◽  
Research Collaboration ◽  
Collaboration Networks

scholarly journals Visualization of clinical teaching citations using social network analysis

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Hakimeh Hazrati ◽  
Shoaleh Bigdeli ◽  
Seyed Kamran Soltani Arabshahi ◽  
Vahideh Zarea Gavgani ◽  
Nafiseh Vahed
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Research Collaboration ◽  
Clinical Teaching ◽  
Clustering Coefficient ◽  
Knowledge Network ◽  
Research Network ◽  
Centrality Measures ◽  
The Usa

Abstract Background Analyzing the previous research literature in the field of clinical teaching has potential to show the trend and future direction of this field. This study aimed to visualize the co-authorship networks and scientific map of research outputs of clinical teaching and medical education by Social Network Analysis (SNA). Methods We Identified 1229 publications on clinical teaching through a systematic search strategy in the Scopus (Elsevier), Web of Science (Clarivate Analytics) and Medline (NCBI/NLM) through PubMed from the year 1980 to 2018.The Ravar PreMap, Netdraw, UCINet and VOSviewer software were used for data visualization and analysis. Results Based on the findings of study the network of clinical teaching was weak in term of cohesion and the density in the co-authorship networks of authors (clustering coefficient (CC): 0.749, density: 0.0238) and collaboration of countries (CC: 0.655, density: 0.176). In regard to centrality measures; the most influential authors in the co-authorship network was Rosenbaum ME, from the USA (0.048). More, the USA, the UK, Canada, Australia and the Netherlands have central role in collaboration countries network and has the vertex co-authorship with other that participated in publishing articles in clinical teaching. Analysis of background and affiliation of authors showed that co-authorship between clinical researchers in medicine filed is weak. Nineteen subject clusters were identified in the clinical teaching research network, seven of which were related to the expected competencies of clinical teaching and three related to clinical teaching skills. Conclusions In order to improve the cohesion of the authorship network of clinical teaching, it is essential to improve research collaboration and co-authorship between new researchers and those who have better closeness or geodisk path with others, especially those with the clinical background. To reach to a dense and powerful topology in the knowledge network of this field encouraging policies to be made for international and national collaboration between clinicians and clinical teaching specialists. In addition, humanitarian and clinical reasoning need to be considered in clinical teaching as of new direction in the field from thematic aspects.

scholarly journals Discovering Research Collaboration Networks from Scientific Digital Libraries and Repositories

2015 ◽  
Vol 53 (2(106)) ◽  
pp. 7-17
Author(s):  
Mieczysław Muraszkiewicz ◽  
Henryk Rybiński ◽  
Piotr Szczepański
Keyword(s):  
Network Analysis ◽  
Digital Libraries ◽  
Research Collaboration ◽  
Formal Model ◽  
Collaboration Networks ◽  
Research Institutions ◽  
Analysis Techniques ◽  
University Of Technology ◽  
Scientific Institutions ◽  
Practical Model

PURPOSE: The purpose of the study is to outline a practical model for discovering research collaboration networks on the basis of data and information stored in scientific digital libraries and repositories. The discovered relationships between researchers, projects, scientific institutions and other scientific entities are used for identifying collaboration networks of researchers and research institutions interested in or working on a given subject. Afterwards, such networks can be subject to various types of network analysis in order to get in-depth knowledge on the networks and their components. APPROACH/METHODS: The method adopted in the study is twofold, that is: (i) it takes into consideration the way of discovering collaboration networks by means of simple tools that have been implemented within the ΩΨR system developed at Warsaw University of Technology; (ii) it develops an outline of a formal model of research collaboration networks that takes into account the specificity of scientific digital libraries and repositories and includes the network analysis techniques for discovering knowledge residing/hidden in the networks. RESULTS AND CONCLUSIONS: The outcome of the research is the outline of a formal model of research collaboration networks that includes: (i) a discovery mechanism for identifying thematically related scientists, projects, research institutions, and other scientific entities; and (ii) a set of network analysis methods for getting in-depth knowledge residing in the networks. The model is implementable and scalable in terms of functionality it offers and the network analysis techniques it includes. The model is founded on a solid ground, which is the ΩΨR system functionality to discover simple collaboration networks, and it is being used for enhancing the ΩΨR system. ORIGINALITY/VALUE: The value of the research is the outline of a general research collaboration networks model that: (i) can help identify, build, and analyse research communities, and thereby increases the scope, value and impact of scientific endeavours on science and society; (ii) is used for enhancing the ΩΨR system.

scholarly journals CollaborationViz: Interactive Visual Exploration of Biomedical Research Collaboration Networks

PLoS ONE ◽  
2014 ◽  
Vol 9 (11) ◽  
pp. e111928 ◽  
Author(s):  
Jiang Bian ◽  
Mengjun Xie ◽  
Teresa J. Hudson ◽  
Hari Eswaran ◽  
Mathias Brochhausen ◽  
...  
Keyword(s):  
Biomedical Research ◽  
Research Collaboration ◽  
Visual Exploration ◽  
Collaboration Networks

scholarly journals Visualization of clinical teaching citations using social network analysis

2021 ◽  
Author(s):  
Hakimeh Hazrati ◽  
Shoaleh Bigdeli ◽  
Seyed Kamran Soltani Arabshahi ◽  
Vahideh Zarea Gavgani ◽  
Nafiseh Vahed
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Research Collaboration ◽  
Clinical Teaching ◽  
Clustering Coefficient ◽  
Knowledge Network ◽  
Research Network ◽  
Centrality Measures ◽  
The Usa

Abstract BackgroundAnalyzing the previous research literature in the filed of clinical teaching has potential to show the trend and future direction of this field. This study aimed to visualize the co-authorship networks and scientific map of research outputs of clinical teaching and medical education by Social Network Analysis (SNA).Methods We Identified 1229 publications on clinical teaching through a systematic search strategy in the Scopus (Elsevier), Web of Science (Clarivate Analytics) and Medline (NCBI/NLM) through PubMed from the year 1980 to 2018.The Ravar PreMap, Netdraw, UCINet and VOSviewer software were used for data visualization and analysis. ResultsBased on the findings of study the network of clinical teaching was weak in term of cohesion and the density in the co-authorship networks of authors (clustering coefficient (CC): 0.749, density: 0.0238) and collaboration of countries (CC: 0.655, density: 0.176). In regard to centrality measures; the most influential authors in the co-authorship network was Rosenbaum ME, from the USA (0.048). More, the USA, the UK, Canada, Australia and the Netherlands have central role in collaboration countries network and has the vertex co-authorship with other that participated in publishing articles in clinical teaching. Analysis of background and affiliation of authors showed that co-authorship between clinical researchers in medicine filed is weak. Nineteen subject clusters were identified in the clinical teaching research network, seven of which were related to the expected competencies of clinical teaching and three related to clinical teaching skills.Conclusions In order to improve the cohesion of the authorship network of clinical teaching, it is essential to improve research collaboration and co-authorship between new researchers and those who have better closeness or geodisk path with others, especially those with the clinical background. To reach to a dense and powerful topology in the knowledge network of this field encouraging policies to be made for international and national collaboration between clinicians and clinical teaching specialists. In addition, humanitarian and clinical reasoning need to be considered in clinical teaching as of new direction in the field from thematic aspects.

scholarly journals Global Research Collaboration for Vapour Intrusion

2021 ◽  
Vol 10 (2) ◽  
pp. 1
Author(s):  
Jeroen Provoost ◽  
Karen Victor
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Research Collaboration ◽  
Research Effort ◽  
Research Network ◽  
Transport Pathway ◽  
The Social ◽  
The Usa ◽  
Global Research

The complexity of the vapour intrusion (VI) transport pathway has received an ever-increased interest worldwide, and an improved and consolidated understanding of the VI issue requires collaboration between international research groups. This study uses the social network analysis methodology, applied to bibliometric authorship for VI research, to discover trends in collaboration, identify lead scientists, organisations, and countries. Furthermore, some of the external factors influencing the collaboration and productivity were assessed. The data suggests that the global research network for VI produced over a time span of 54 years 566 publications via 157 sources. The research network is composed of 437 organisations and 1053 authors from 33 countries. This suggests an increasingly active international collaborative research effort. However, inter-continental cooperation is much less than continental. The top five most central countries in the network are the USA, followed by Canada, China, The Netherlands, and Italy. The researchers with the most publications are from these five countries as well as the top organisations. The social network analysis conducted shows a good approximation of the collaborative structure for the key countries, organisations and researchers involved. Since 2010, the research community has become more stable.

scholarly journals 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

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Vasiliki Kiparoglou ◽  
Laurence A. Brown ◽  
Helen McShane ◽  
Keith M. Channon ◽  
Syed Ghulam Sarwar Shah
Keyword(s):  
Translational Research ◽  
Biomedical Research ◽  
Health Research ◽  
Research Collaboration ◽  
Research Policy ◽  
Geometric Mean ◽  
Policy Formulation ◽  
Research Centre ◽  
Collaboration Networks ◽  
Research Publications

Abstract 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.

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