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.

Social network analysis and data visualization of MIS international collaboration in Taiwan

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Yung-Ting Chuang ◽  
Yi-Hsi Chen
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
International Collaboration ◽  
Research Productivity ◽  
Research Collaboration ◽  
Clustering Algorithms ◽  
The United States ◽  
Content Type ◽  
Collaboration Patterns

PurposeThe purpose of this paper is to apply social network analysis (SNA) to study faculty research productivity, to identify key leaders, to study publication keywords and research areas and to visualize international collaboration patterns and analyze collaboration research fields from all Management Information System (MIS) departments in Taiwan from 1982 to 2015.Design/methodology/approachThe authors first retrieved results encompassing about 1,766 MIS professors and their publication records between 1982 and 2015 from the Ministry of Science and Technology of Taiwan (MOST) website. Next, the authors merged these publication records with the records obtained from the Web of Science, Google Scholar, IEEE Xplore, ScienceDirect, Airiti Library and Springer Link databases. The authors further applied six network centrality equations, leadership index, exponential weighted moving average (EWMA), contribution value and k-means clustering algorithms to analyze the collaboration patterns, research productivity and publication patterns. Finally, the authors applied D3.js to visualize the faculty members' international collaborations from all MIS departments in Taiwan.FindingsThe authors have first identified important scholars or leaders in the network. The authors also see that most MIS scholars in Taiwan tend to publish their papers in the journals such as Decision Support Systems and Information and Management. The authors have further figured out the significant scholars who have actively collaborated with academics in other countries. Furthermore, the authors have recognized the universities that have frequent collaboration with other international universities. The United States, China, Canada and the United Kingdom are the countries that have the highest numbers of collaborations with Taiwanese academics. Lastly, the keywords model, system and algorithm were the most common terms used in recent years.Originality/valueThis study applied SNA to visualize international research collaboration patterns and has revealed some salient characteristics of international cooperation trends and patterns, leadership networks and influences and research productivity for faculty in Information Management departments in Taiwan from 1982 to 2015. In addition, the authors have discovered the most common keywords used in recent years.

Research Activities and Networks in CAIS Conferences for the Period of 1993- 2015: Social Network Analysis

1969 ◽  
Author(s):  
Kwan Yi ◽  
Tao Jin ◽  
Ping Li
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Collaborative Research ◽  
Information Science ◽  
Research Collaboration ◽  
Collaboration Network ◽  
Research Activities ◽  
Canadian Association ◽  
Collaborative Activities

Since 1973 the Canadian Association for Information Science (CAIS/ACSI) has consecutively held 43 annual conferences. The purpose of this study is to better understand the research and collaborative activities in the community of CAIS conferences, based on a social network analysis (SNA) approach. A total of 827 papers from 778 authors have been presented in CAIS for the period of 1993 to 2015, in association with 209 different organizations and 25 countries. A component analysis that has been applied to the collaboration network has discovered research collaboration patterns. This study contributes to discovering collaborative research activities and formation through the CAIS conference and to the literature of the scientific collaboration in the LIS field. Depuis 1973, l'Association canadienne de sciences de l'information (ACSI/CAIS) a tenu 43 congrès annuels consécutifs. Le but de cette étude est de mieux comprendre les activités de recherche et de collaboration dans la communauté de l’ACSI, à l’aide d’une approche d’analyse des réseaux sociaux (ARS). Un total de 827 articles de 778 auteurs ont été présentés à l’ACSI dans la période 1993-2015, en association avec 209 organisations différentes et 25 pays. L’analyse des composantes du réseau de collaboration met en lumière l’existence de patrons de collaboration de recherche au sein de la communauté. Cette étude contribue à l’étude des activités  de collaboration au sein des congrès de l’ACSI ainsi qu’à la littérature sur la collaboration scientifique dans le domaine BSI.

scholarly journals Social Network Analysis to Assess the Impact of the CTSA on Biomedical Research Grant Collaboration

2014 ◽  
Vol 8 (2) ◽  
pp. 150-154 ◽  
Author(s):  
Radhakrishnan Nagarajan ◽  
Charlotte A. Peterson ◽  
Jane S. Lowe ◽  
Stephen W. Wyatt ◽  
Timothy S. Tracy ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Biomedical Research ◽  
The Impact ◽  
Research Grant

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 A Transnational Research Collaboration: A Social Network Analysis and Perspectives on Our Community of Practice

Quest ◽  
2021 ◽  
pp. 1-15
Author(s):  
Phillip Ward ◽  
Erhan Devrilmez ◽  
Shiri Ayvazo ◽  
Fatih Dervent ◽  
Yaohui He ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Community Of Practice ◽  
Research Collaboration

Social Media Metrics in an Academic Setup

2017 ◽  
pp. 116-130
Author(s):  
Tasleem Arif ◽  
Rashid Ali
Keyword(s):  
Social Media ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Present Status ◽  
The Internet ◽  
Collaboration Networks ◽  
Different Types ◽  
Network Metrics ◽  
Network Analysis Metrics

Social media is perhaps responsible for largest share of traffic on the Internet. It is one of the largest online activities with people from all over the globe making its use for some sort of activity. The behaviour of these networks, important actors and groups and the way individual actors influence an idea or activity on these networks, etc. can be measured using social network analysis metrics. These metrics can be as simple as number of likes on Facebook or number of views on YouTube or as complex as clustering co-efficient which determines future collaborations on the basis of present status of the network. This chapter explores and discusses various social network metrics which can be used to analyse and explain important questions related to different types of networks. It also tries to explain the basic mathematics behind the working of these metrics. The use of these metrics for analysis of collaboration networks in an academic setup has been explored and results presented. A new metric called “Average Degree of Collaboration” has been defined to quantify collaborations within institutions.

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