How to identify key players that contribute to resilient performance: A social network analysis perspective

2022 ◽  
Vol 148 ◽  
pp. 105648
Author(s):  
Vanessa Becker Bertoni ◽  
Tarcisio Abreu Saurin ◽  
Flávio Sanson Fogliatto
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Key Players

Information access and sharing among prosthetics and orthotics faculty in Ghana and the United States

2020 ◽  
pp. 030936462095882
Author(s):  
Cody L McDonald ◽  
Henry Larbi ◽  
Sarah Westcott McCoy ◽  
Deborah Kartin
Keyword(s):  
United States ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Information Exchange ◽  
Information Access ◽  
The United States ◽  
Exchange Networks ◽  
Key Players ◽  
Internal Connections

Background: Information access is essential for quality healthcare provision and education. Despite technological advances, access to prosthetics and orthotics information in low- and middle-income countries is not ubiquitous. The current state of information access, availability, and exchange among prosthetics and orthotics faculty is unknown. Objectives: Describe information exchange networks and access at two prosthetics and orthotics programs in Ghana and the United States. Study design: Cross-sectional survey, social network analysis. Methods: An online survey of faculty at two prosthetics and orthotics programs using REDCap. The survey included a social network analysis, demographics, and prosthetics and orthotics information resources and frequency of use. Descriptive statistics were calculated. Results: Twenty-one faculty members completed the survey (84% response). Ghanaian faculty were on average younger (median Ghana: 27 years, United States: 43 years), had less teaching experience, and had less education than US faculty. Textbooks were the most commonly used resource at both programs. The Ghanaian network had more internal connections with few outside sources. The US network had fewer internal connections, relied heavily upon four key players, and had numerous outside contacts. Conclusion: Ghana and US faculty have two distinct information exchange networks. These networks identify key players and barriers to dissemination among faculty to promote successful knowledge translation of current scientific literature and technology development. Social network analysis may be a useful method to explore information sharing among prosthetics and orthotics faculty, and identify areas for further study.

scholarly journals Passing Network Analysis of Positional Attack Formations in Handball

2019 ◽  
Vol 70 (1) ◽  
pp. 209-221 ◽  
Author(s):  
Florian Korte ◽  
Martin Lames
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Suitable Method ◽  
Interaction Patterns ◽  
Optimal Position ◽  
Key Players ◽  
Sport Teams ◽  
The Individual ◽  
General Balance

Abstract The aim of this study was to characterize handball from a social network analysis perspective by analyzing 22 professional matches from the 2018 European Men's Handball Championship. Social network analysis has proven successful in the study of sports dynamics to investigate the interaction patterns of sport teams and the individual involvement of players. In handball, passing is crucial to establish an optimal position for throwing the ball into the goal of the opponent team. Moreover, different tactical formations are played during a game, often induced by two-minute suspensions or the addition of an offensive player replacing the goalkeeper as allowed by the International Handball Federation since 2016. Therefore, studying the interaction patterns of handball teams considering the different playing positions under various attack formations contributes to the tactical understanding of the sport. Degree and flow centrality as well as density and centralization values were computed. As a result, quantification of the contribution of individual players to the overall organization was achieved alongside the general balance in interplay. We identified the backcourt as the key players to structure interplay across tactical formations. While attack units without a goalkeeper were played longer, they were either more intensively structured around back positions (7 vs. 6) or spread out (5 + 1 vs. 6). We also found significant differences in the involvement of wing players across formations. The additional pivot in the 7 vs. 6 formation was mostly used to create space for back players and was less involved in interplay. Social network analysis turned out as a suitable method to govern and quantify team dynamics in handball.

scholarly journals Social Network Analysis of Terrorist Networks

2020 ◽  
Vol 9 (3) ◽  
pp. 2553-2559
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Past Research ◽  
Temporal Analysis ◽  
Centrality Measures ◽  
Underlying Structure ◽  
Key Players ◽  
Terrorist Networks ◽  
Using Data

Terrorist Activities worldwide has led to the development of sophisticated methodologies for analyzing terrorist groups and networks. Ongoing and past research has found that Social Network Analysis (SNA) is most effective method for predictive counter-terrorism. Social Network Analysis (SNA) is an approach towards analyzing the terrorist networks to better understand the underlying structure of a network and to detect key players within the network and their links throughout the network. It is also need of the hour to convert available raw data into valuable information for the purpose of global security. Comparative study among SNA tools testify their applicability and usefulness for data gathered through online and offline social sources. However it is advised to incorporate temporal analysis using data mining methods, to improve the capability of SNA tools to handle dynamic social media data. This paper examine various aspects of Social Network Analysis as applied to terrorism, taking empirical data, and open source data based studies into account. This work primarily focuses on different types of decentralized terrorist networks and nodes. The nodes can be classified as organizations, places or persons. We take help of varied centrality measures to identify key players in this network.

scholarly journals A Technique to Identify Key Players that Helps to Improve Businesses Using Multilayer Social Network Analysis

2018 ◽  
Vol 7 (4) ◽  
pp. 98-102
Author(s):  
Aftab Farooq ◽  
◽  
Usman Akram ◽  
Gulraiz Javaid Joyia ◽  
Chaudhry Naeem Akbar
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Key Players

Analisis Pola Persebaran Pornografi pada Media Sosial dengan Social Network Analysis

2018 ◽  
Vol 9 (1) ◽  
pp. 43-52 ◽  
Author(s):  
Muchamad Taufiq Anwar
Keyword(s):  
Social Media ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Distribution Pattern ◽  
Negative Effects ◽  
Key Players

The rise of social media had opened up an easy and fast way to distribute pornographic content through it. Although the negative effects linked to porn consumption are still inconclusive, government had established regulation regarding porn creation, distribution, and ownership. Unfortunately, the regulation is not well run. Porn are freely distributed through social media without any reaction from the authorities. This reseach aims to understand the distribution pattern and to find key players in the distribution of porn in social media using Social Network Analysis (SNA) so that mitigative actions could be made. Result shows that porn were first published by popular ‘Publisher’ accounts, re-shared by other publisher accounts or ‘Retweeters’, and unidirectionally consumed by followers (‘Consumers’). Interpretation and research limitations were discussed.

scholarly journals Evaluation of nosocomial infections through contact patterns in a small animal hospital using social network analysis and genotyping techniques

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Amara Churak ◽  
Chaithep Poolkhet ◽  
Yutaka Tamura ◽  
Tomomi Sato ◽  
Akira Fukuda ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Nosocomial Infections ◽  
Animal Movement ◽  
Small Animal ◽  
Contact Network ◽  
Flight Mass Spectrometry ◽  
Key Players ◽  
Key Nodes

AbstractNosocomial infections or hospital-acquired infections (HAIs) are common health problems affecting patients in human and animal hospitals. Herein, we hypothesised that HAIs could be spread through human and animal movement, contact with veterinary medical supplies, equipment, or instruments. We used a combination of social network analysis and genotyping techniques to find key players (or key nodes) and spread patterns using Escherichia coli as a marker. This study was implemented in the critical care unit, outpatient department, operation room, and ward of a small animal hospital. We conducted an observational study used for key player determination (or key node identification), then observed the selected key nodes twice with a one-month interval. Next, surface swabs of key nodes and their connecting nodes were analysed using bacterial identification, matrix-assisted laser desorption/ionisation-time of flight mass spectrometry, and pulsed-field gel electrophoresis. Altogether, our results showed that veterinarians were key players in this contact network in all departments. We found two predominant similarity clusters; dendrogram results suggested E. coli isolates from different time points and places to be closely related, providing evidence of HAI circulation within and across hospital departments. This study could aid in limiting the spread of HAIs in veterinary and human hospitals.

scholarly journals ANALISIS JARINGAN TRANSFER PEMAIN BOLA MENGGUNAKAN METODE SOCIAL NETWORK ANALYSIS (STUDI KASUS : LIGA SPANYOL (LA LIGA) TAHUN 2015 – 2020)

2020 ◽  
Vol 17 (1) ◽  
pp. 88-95
Author(s):  
Ni Made Distiara Landephy Aryashila ◽  
Silvyana Nur Haliza ◽  
Naufal Farras Maulana ◽  
Doni Achmad Heniawan ◽  
Yudianto Yudianto
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Basic Concept ◽  
Closeness Centrality ◽  
Degree Centrality ◽  
Improve Performance ◽  
The Social ◽  
The World ◽  
Key Players

Football is a popular sport that is loved by a lot of society in the world, ranging from children to adult is very enthusiastic when discussing about soccer. The process of buying and transferring players is one element that can’t be separated in football, this process is done to improve performance and replace players who move to other clubs. Spanish league or known as La Liga is one of the major league that often transfers player, information regarding player transfers and the club itself can be seen in each season on the website transfermarkt.com. In this study we chose the Spanish League as an object of research, we use the Social Network Analysis Basic Concept technique to determine the key players of each club and players in the Spanish League in the 2015-2020 period by analyzing degree centrality, closeness centrality, dan betweenness centrality. the results of this study were displayed  Sevilla FC as a club key player, and Juanfran as a key player player

scholarly journals Informatics for COVID-19 in New York and California

2021 ◽  
pp. 1-14
Author(s):  
Seungil Yum
Keyword(s):  
New York ◽  
Social Networks ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Communication Networks ◽  
Crucial Role ◽  
Essential Role ◽  
The Us ◽  
Key Players

Abstract Objective: This study explores how social networks for COVID-19 are differentiated by regions. Methods: This study employs social network analysis for Twitter in New York and California. Results: National key players play an important role in New York, while regional key players exert a significant impact on California. Some key players, such as the US president, play an essential role in both New York and California. Hispanic key players play a crucial role in California. Each group is more likely to show communication networks within groups in New York, while it is more apt to exhibit communication networks across groups in California. Government players play a different role in social networks according to regions. Conclusions: Governments should understand how social networks for COVID-19 are differentiated by regions to control the ongoing pandemic effectively.

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