Social network analysis of scientific collaborations across different subject fields

Bozdogan, Hamparsum; Akbilgiç, Oğuz

doi:10.3233/isu-130715

Cited by 8 publications

(8 citation statements)

References 22 publications

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“…We calculated degree of centrality, closeness, betweenness for author, institution and country networks using Ucinet 6.0. Centrality measures help the researcher to determine which nodes are important to be kept in the network [ 18 – 20 ]. Degree of centrality of a node is characterized as the number of ties or edges close to a given node, that is, degree of centrality equals the number of coauthors of a given author [ 19 , 20 ].…”

Section: Methodsmentioning

confidence: 99%

The Global Research Collaboration of Network Meta-Analysis: A Social Network Analysis

Catalá-López

Alonso-Arroyo

et al. 2016

PLoS ONE

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Background and ObjectiveResearch collaborations in biomedical research have evolved over time. No studies have addressed research collaboration in network meta-analysis (NMA). In this study, we used social network analysis methods to characterize global collaboration patterns of published NMAs over the past decades.MethodsPubMed, EMBASE, Web of Science and the Cochrane Library were searched (at 9th July, 2015) to include systematic reviews incorporating NMA. Two reviewers independently selected studies and cross-checked the standardized data. Data was analyzed using Ucinet 6.0 and SPSS 17.0. NetDraw software was used to draw social networks.Results771 NMAs published in 336 journals from 3459 authors and 1258 institutions in 49 countries through the period 1997–2015 were included. More than three-quarters (n = 625; 81.06%) of the NMAs were published in the last 5-years. The BMJ (4.93%), Current Medical Research and Opinion (4.67%) and PLOS One (4.02%) were the journals that published the greatest number of NMAs. The UK and the USA (followed by Canada, China, the Netherlands, Italy and Germany) headed the absolute global productivity ranking in number of NMAs. The top 20 authors and institutions with the highest publication rates were identified. Overall, 43 clusters of authors (four major groups: one with 37 members, one with 12 members, one with 11 members and one with 10 members) and 21 clusters of institutions (two major groups: one with 62 members and one with 20 members) were identified. The most prolific authors were affiliated with academic institutions and private consulting firms. 181 consulting firms and pharmaceutical industries (14.39% of institutions) were involved in 199 NMAs (25.81% of total publications). Although there were increases in international and inter-institution collaborations, the research collaboration by authors, institutions and countries were still weak and most collaboration groups were small sizes.ConclusionScientific production on NMA is increasing worldwide with research leadership of Western countries (most notably, the UK, the USA and Canada). More authors, institutions and nations are becoming involved in research collaborations, but frequently with limited international collaborations.

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Section: Methodsmentioning

confidence: 99%

The Global Research Collaboration of Network Meta-Analysis: A Social Network Analysis

Catalá-López

Alonso-Arroyo

et al. 2016

PLoS ONE

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“…To establish which users had a larger number of relationships and were more active on Twitter, we utilized the social network analysis measures of degree centrality, betweenness centrality, closeness centrality, and modularity. Several authors have understood these measures to be suitable and clear indicators of influencers on social media (Bozdogan & Akbilgic, 2013;Gökçe et al, 2014;Himelboim & Golan, 2019;Liu et al, 2017;Sevin & Manor, 2019).…”

Section: Social Network Analysismentioning

confidence: 99%

Key Influencers in Public Diplomacy 2.0: A Country-Based Social Network Analysis

Ingenhoff

Calamai

Sevin

2021

Social Media + Society

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This article presents a study of Twitter-based communication in order to identify key influencers and to assess the role of their communication in shaping country images. The analysis is based on a 2-month dataset comprised of all tweets including hashtags of the three countries selected for this study: Austria, Switzerland, and the Netherlands. Following a two-step flow model of communication, we initially identified the influential Twitter users in all three countries based on their centrality measures. Subsequently, we carried out a qualitative content analysis of tweets posted by these influential users. Finally, we assessed the similarities and differences across the three country cases. This article offers new insights into public diplomacy 2.0 activities by discussing influence within the context of country images and demonstrating how opinion leaders can play a more dominant role than states or other political actors in creating and disseminating content related to country image. The findings also provide practical insights in the production of a country’s image and its representation on new media platforms.

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“…There is a study about the interaction and the degree of collaboration between di®erent disciplines through the analysis of social networks from a database provided by the O±ce of Scienti¯c and Technology Information of the US Department of Energy using statistical techniques based on the graph theory. 27 The study considers the social network as a set of nodes (people, institutions and countries) and edges (relationships between nodes). They created two di®erent networks, one for the publications between 1980 and 2000 and other one for 2000-2012.…”

Section: State Of the Artmentioning

confidence: 99%

Analysis of Internal and External Academic Collaboration in an Institution Through Graph Theory

Sosa

Domínguez

Castellanos-Bolaños

et al. 2020

Vietnam J. Comp. Sci.

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This paper presents an analysis of scientific collaboration through graph theory, based on a previous study focused on the collaborative work of researchers within an institution. This proposal also exposes the representation of inter-institutional collaboration of research groups, combining graph theory and data mining. The state of the art relates the concepts of scientific production, digital repositories, interoperability between repositories, the law of Open Science in Mexico, the theory of graphs and their use in previous studies for the analysis of scientific collaboration, and the definition of research groups in Mexico. Furthermore, the methodology uses elements of knowledge extraction for data mining, involving recovery, processing and visualization. Results present the collaboration status at the Universidad Autónoma de Yucatán, internally and externally, by the research groups. Internally, 22 groups were found and each researcher collaborates with six other professors within the institution, on average. In addition, consolidated research groups are those with the highest level of production and collaboration at national and international level, compared to the groups with less consolidation.

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Social network analysis of scientific collaborations across different subject fields

Cited by 8 publications

References 22 publications

The Global Research Collaboration of Network Meta-Analysis: A Social Network Analysis

The Global Research Collaboration of Network Meta-Analysis: A Social Network Analysis

Key Influencers in Public Diplomacy 2.0: A Country-Based Social Network Analysis

Analysis of Internal and External Academic Collaboration in an Institution Through Graph Theory

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