Applying Social Network Analysis and Centrality Measures to Improve Information Flow Analysis

Author(s):  
Stephan Kiesling ◽  
Jil Klünder ◽  
Diana Fischer ◽  
Kurt Schneider ◽  
Kai Fischbach
Author(s):  
Othieno Joseph ◽  
Mugivane I Fred ◽  
Nyaga Philip ◽  
Ogara William ◽  
Muchemi Gerald

Climate change is negatively affecting livelihoods dependent on rain fed agriculture in Kenya. Adaptation through adoption of appropriate agricultural technologies is necessary. Communication plays a critical role in dissemination of climate change information and adaptation. The study applied social network analysis (SNA) using NodeXL computer programme to generate socio-grams that showed patterns of information flow from which important network and individual characteristic of the opinion leaders were described. This study shows that SNA is applicable in climate change communication to identify opinion leaders by mapping out information flow patterns and using measures of centrality.Int. J. Agril. Res. Innov. & Tech. 6 (1): 1-7, June, 2016


2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Hakimeh Hazrati ◽  
Shoaleh Bigdeli ◽  
Seyed Kamran Soltani Arabshahi ◽  
Vahideh Zarea Gavgani ◽  
Nafiseh Vahed

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.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
José Alberto Benítez-Andrades ◽  
Tania Fernández-Villa ◽  
Carmen Benavides ◽  
Andrea Gayubo-Serrenes ◽  
Vicente Martín ◽  
...  

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.


2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Nandun Madhusanka Hewa Welege ◽  
Wei Pan ◽  
Mohan Kumaraswamy

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.


2019 ◽  
Vol 105 (1) ◽  
pp. 83-96
Author(s):  
Vincent Chollier

This article aims at presenting a methodology for Social Network Analysis (SNA) applied to Egyptology and ancient societies studies, with its benefits and issues. One of the big issues dealing with social relationships in ancient Egypt lies in the use of kinship terminology defining relations outside the family. In that sense, SNA allows researchers to partially set aside links values contrary to traditional genealogical studies, especially for the graphical projection. Thus, biological and social brothers do not have to be distinguished using this method, although this distinction is often impossible to do. It then presents an empirical method developed using this branch of sociology on an Egyptological dataset dating back from the New Kingdom. With the help of centrality measures, SNA enabled attention to be drawn to secondary role characters at the first sight of the hieroglyphic documentation. However, studying such a type of documentation requires a cautious approach, especially regarding the nature and aim of the sources available.


2017 ◽  
Vol 56 (4) ◽  
pp. 589-618 ◽  
Author(s):  
Iris Reychav ◽  
Daphne Ruth Raban ◽  
Roger McHaney

The current empirical study examines relationships between network measures and learning performance from a social network analysis perspective. We collected computerized, networking data to analyze how 401 junior high students connected to classroom peers using text- and video-based material on iPads. Following a period of computerized interaction, learning assessments were taken at individual or group consensus levels. Social network analysis suggested highly connected students became information sources with higher individual assessment achievements. Students receiving information from central sources exhibited higher achievements in group consensus treatments. Students acting as bridges between others on the network regulated themselves better and achieved higher academic outcomes. However, a subset of students were motivated by social interaction rather than learning task. This finding, consistent with general social networking research, cautions educators to ensure socializing does not override learning objectives when using classroom social networking.


2021 ◽  
Vol 11 (4) ◽  
pp. 2964-2975
Author(s):  
Zahra Batool ◽  
Muhammad Junaid ◽  
Muhammad Naeem ◽  
Mehmood Ahmed ◽  
Luqman Shah ◽  
...  

Social network analysis has been increasingly employed to study patterns in diverse areas of disciplines such as crowd management, air passenger and freight transportation, business modelling and analysis, online social movements and bioinformatics. Over the years, human disease networks have been studied to analyze Human Disease, Genotype, and Phenotype networks. This study explores human Disease Network based on their symptoms by employing different social network analysis such as centrality measures of network, community detection, overlapping communities. We studied relationships of symptoms with diseases on meso-level in order to detect comorbidity pattern of communities in disease network. This help us to understand the underlying patterns of diseases based on symptoms and find out that how different disease communities are correlated by detecting overlapping communities.


2014 ◽  
Vol 30 (3) ◽  
pp. 817 ◽  
Author(s):  
Kyung Jin Park ◽  
Joohyun Lim ◽  
Ki Young Kim

<p>In this study, we examined how income shifting performs among affiliates in a business group to maximize the benefits of the entire business group in terms of minimizing the tax burden, with a particular focus on the direction of income shifting between affiliates within the business group. We find that tax-related decision-making for the entire business group is affected by the relationships between the affiliated firms, that is, the ownership structure of the whole business group. To analyze the ownership structure, we use centrality measures in a social network analysis. The results show that affiliates with the higher outdegree-centrality; that is, firms investing more shareholdings in other affiliates have a tendency to perform more income shifting. On the other hand, the affiliates with high indegree-centrality, that is, firms which are owned by other affiliates, were revealed to be given the income shifting from other affiliated firms to minimize the tax burden of the entire business group.</p>


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