Identification of Centrality Measures in Social Network using Network Science

2019 ◽  
Author(s):  
Amit Kumar Yadav ◽  
Rahul Johari ◽  
Raman Dahiya
Keyword(s):  
Social Network ◽  
Network Science ◽  
Centrality Measures

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.

Comparison and Application of Metrics That Define the Components Modularity in Complex Products

2008 ◽  
Author(s):  
Qi D. Van Eikema Hommes
Keyword(s):  
Social Network ◽  
Centrality Measures ◽  
Software Systems ◽  
Network Centrality ◽  
Good Pair ◽  
Centrality Metrics ◽  
The Social ◽  
Social Network Centrality ◽  
Sample Test

As the content and variety of technology increases in automobiles, the complexity of the system increases as well. Decomposing systems into modules is one of the ways to manage and reduce system complexity. This paper surveys and compares a number of state-of-art components modularity metrics, using 8 sample test systems. The metrics include Whitney Index (WI), Change Cost (CC), Singular value Modularity Index (SMI), Visibility-Dependency (VD) plot, and social network centrality measures (degree, distance, bridging). The investigation reveals that WI and CC form a good pair of metrics that can be used to assess component modularity of a system. The social network centrality metrics are useful in identifying areas of architecture improvements for a system. These metrics were further applied to two actual vehicle embedded software systems. The first system is going through an architecture transformation. The metrics from the old system revealed the need for the improvements. The second system was recently architected, and the metrics values showed the quality of the architecture as well as areas for further improvements.

scholarly journals A case study of university student networks and the COVID-19 pandemic using a social network analysis approach in halls of residence

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
José Alberto Benítez-Andrades ◽  
Tania Fernández-Villa ◽  
Carmen Benavides ◽  
Andrea Gayubo-Serrenes ◽  
Vicente Martín ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
University Students ◽  
Methodological Approach ◽  
Centrality Measures ◽  
Structural Behaviour ◽  
Cross Sectional ◽  
Depth Analysis ◽  
The University

AbstractThe COVID-19 pandemic has meant that young university students have had to adapt their learning and have a reduced relational context. Adversity contexts build models of human behaviour based on relationships. However, there is a lack of studies that analyse the behaviour of university students based on their social structure in the context of a pandemic. This information could be useful in making decisions on how to plan collective responses to adversities. The Social Network Analysis (SNA) method has been chosen to address this structural perspective. The aim of our research is to describe the structural behaviour of students in university residences during the COVID-19 pandemic with a more in-depth analysis of student leaders. A descriptive cross-sectional study was carried out at one Spanish Public University, León, from 23th October 2020 to 20th November 2020. The participation was of 93 students, from four halls of residence. The data were collected from a database created specifically at the university to "track" contacts in the COVID-19 pandemic, SiVeUle. We applied the SNA for the analysis of the data. The leadership on the university residence was measured using centrality measures. The top leaders were analyzed using the Egonetwork and an assessment of the key players. Students with higher social reputations experience higher levels of pandemic contagion in relation to COVID-19 infection. The results were statistically significant between the centrality in the network and the results of the COVID-19 infection. The most leading students showed a high degree of Betweenness, and three students had the key player structure in the network. Networking behaviour of university students in halls of residence could be related to contagion in the COVID-19 pandemic. This could be described on the basis of aspects of similarities between students, and even leaders connecting the cohabitation sub-networks. In this context, Social Network Analysis could be considered as a methodological approach for future network studies in health emergency contexts.

A network case of knowledge brokering

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Joelle Rodway ◽  
Stephen MacGregor ◽  
Alan Daly ◽  
Yi-Hwa Liou ◽  
Susan Yonezawa ◽  
...  
Keyword(s):  
Social Network ◽  
Learning Community ◽  
Knowledge Exchange ◽  
Point Of View ◽  
Network Activity ◽  
Centrality Measures ◽  
Knowledge Brokering ◽  
Content Type ◽  
Knowledge Brokers ◽  
Over Time

PurposeThe purpose of this paper is two-fold: (1) to offer a conceptual understanding of knowledge brokering from a sociometric point-of-view; and (2) to provide an empirical example of this conceptualization in an education context.Design/methodology/approachWe use social network theory and analysis tools to explore knowledge exchange patterns among a group of teachers, instructional coaches and administrators who are collectively seeking to build increased capacity for effective mathematics instruction. We propose the concept of network activity to measure direct and indirect knowledge brokerage through the use of degree and betweenness centrality measures. Further, we propose network utility—measured by tie multiplexity—as a second key component of effective knowledge brokering.FindingsOur findings suggest significant increases in both direct and indirect knowledge brokering activity across the network over time. Teachers, in particular, emerge as key knowledge brokers within this networked learning community. Importantly, there is also an increase in the number of resources exchanged through network relationships over time; the most active knowledge brokers in this social ecosystem are those individuals who are exchanging multiple forms of knowledge.Originality/valueThis study focuses on knowledge brokering as it presents itself in the relational patterns among educators within a social ecosystem. While it could be that formal organizational roles may encapsulate knowledge brokering across physical structures with an education system (e.g. between schools and central offices), these individuals are not necessarily the people who are most effectively brokering knowledge across actors within the broader social network.

Social network analysis applications in sustainable construction and built environment management: a review

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nandun Madhusanka Hewa Welege ◽  
Wei Pan ◽  
Mohan Kumaraswamy
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Built Environment ◽  
Methodological Approach ◽  
Relevant Literature ◽  
Sustainable Construction ◽  
Centrality Measures ◽  
Environment Management ◽  
Content Type

PurposeApplications of social network analysis (SNA) are evidently popular amongst scholars for mapping stakeholder and other relational networks in improving the sustainability of construction activities and the resulting built environment. Nevertheless, the literature reveals a lack of thorough understanding of optimal SNA applications in this field. Therefore, this paper aims to convey a comprehensive critical review of past applications of SNA in this field.Design/methodology/approach95 relevant journal papers were initially identified from the “Web of Science” database and a bibliometric analysis was carried out using the “VOS Viewer” software. The subsequent in-depth review of the SNA methods, focussed on 24 specifically relevant papers selected from these aforesaid 95 papers.FindingsA significant growth of publications in this field was identified after 2014, especially related to topics on stakeholder management. “Journal of Cleaner Production”, “International Journal of Project Management” and “Sustainability” were identified as the most productive sources in this field, with the majority of publications from China. Interviews and questionnaires were the popular data collection methods while SNA “Centrality” measures were utilised in over 70% of the studies. Furthermore, potential areas were noted, to improve the mapping and thereby provide useful information to managers who could influence relevant networks and consequentially better sustainability outcomes, including those enhanced by collaborative networks.Originality/valueCloser collaboration has been found to help enhance sustainability in construction and built environment, hence attracting research interest amongst scholars on how best to enable this. SNA is established as a significant methodological approach to analysing interrelationships and collaborative potential in general. In a pioneering application here, this paper initiates the drawing together of findings from relevant literature to provide useful insights for future researchers to comprehensively identify, compare and contrast the applications of SNA techniques in construction and built environment management from a sustainability viewpoint.

The Digital Age and the Future of Social Network Science and Engineering

2014 ◽  
Vol 102 (12) ◽  
pp. 1873-1877 ◽  
Author(s):  
Jessica C. Flack ◽  
Raissa M. D'Souza
Keyword(s):  
Social Network ◽  
Network Science ◽  
Digital Age ◽  
Science And Engineering ◽  
The Future

Classifying the Influential Individuals in Multi-Layer Social Networks

2019 ◽  
Vol 8 (1) ◽  
pp. 21-32
Author(s):  
Ruchi Mittal ◽  
M.P.S Bhatia
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Information Diffusion ◽  
Real Life ◽  
Single Layer ◽  
Machine Learning Techniques ◽  
Centrality Measures ◽  
Learning Techniques ◽  
Modes Of Interaction ◽  
Source Of Information

Nowadays, social media is one of the popular modes of interaction and information diffusion. It is commonly found that the main source of information diffusion is done by some entities and such entities are also called as influencers. An influencer is an entity or individual who has the ability to influence others because of his/her relationship or connection with his/her audience. In this article, we propose a methodology to classify influencers from multi-layer social networks. A multi-layer social network is the same as a single layer social network depict that it includes multiple properties of a node and modeled them into multiple layers. The proposed methodology is a fusion of machine learning techniques (SVM, neural networks and so on) with centrality measures. We demonstrate the proposed algorithm on some real-life networks to validate the effectiveness of the approach in multi-layer systems.

The Role of Social Networking in Capital Sourcing

2019 ◽  
pp. 097215091986886 ◽  
Author(s):  
Ameeta Jaiswal-Dale ◽  
Fanny Simon-Lee ◽  
Giovanna Zanotti ◽  
Peter Cincinelli
Keyword(s):  
Social Networks ◽  
Social Network ◽  
Social Networking ◽  
Early Stage ◽  
Centrality Measures ◽  
Spontaneous Growth ◽  
Empirical Results ◽  
Road Map ◽  
The Social

The aim of this research is to apply the tool of social network analysis to situations in capital sourcing, including early stage financing. The study is conducted within the social network of Medical Alley Association of Minnesota (MAA). We investigate the correlation between the main centrality measures: closeness, degree and betweenness, and the amount of funding received by the 163 MAA members during 2009–2012. Companies benefit from their social network to get access to better financing. The empirical results also provide a road map to encourage the sponsored or spontaneous growth of other social networks in related fields. Despite the financial crisis, the empirical results show how competition works when firms have established relations with others. Where an intersection occurs is merely an empirical curiosity and the causation resides in the intersection of relations. The relation that intersects on an organization determines the player’s competitive advantage.

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