scholarly journals Characterizing Stakeholders of Aging-in-Place through Social Network Analysis: A Study of Nanjing, China

2019 ◽  
Vol 11 (23) ◽  
pp. 6722
Author(s):  
Shenghua Zhou ◽  
S. Thomas Ng ◽  
Dezhi Li ◽  
Jiankun Zhang ◽  
Jie Fan ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Wide Spectrum ◽  
Aging In Place ◽  
Policy Implications ◽  
Third Party ◽  
Pilot Programs ◽  
Excess Power ◽  
High Level

China currently has an elderly population of 249 million with over 97% of them ending up aging in place. Although various regional pilot programs have been conducted, a sustainable aging-in-place system has not been established to effectively and efficiently provide aging services in many cities of China. The characteristics of stakeholder networks in the aging-in-place systems have not attracted great attention from researchers. This research applies social network analysis to characterize the interactions of stakeholders in aging-in-place systems to facilitate cooperation and coordination amongst them. Using Nanjing as a case study, 23 stakeholders in Nanjing’s aging-in-place system are identified, such as the Aging Affairs Committee, Aging-in-Place Service Association, and aging-in-place service centers; and then the relationship networks of these stakeholders in terms of communication, supervision, and trust are developed and analyzed. The results show that the aging-in-place system suffers from certain defects, including the loose connection of government departments, redundant information channels, low trustworthiness of certain aging-in-place service centers, poor credibility of third-party training and assessment institutions, and excess power of the industry association. To tackle these issues, a wide spectrum of actionable measures applicable to Nanjing’s conditions, as well as high-level policy implications for other cities of China, are proposed for augmenting the communication, supervision, and trust among stakeholder groups.

scholarly journals Nursing Students’ Subjective Happiness: A Social Network Analysis

2021 ◽  
Vol 18 (21) ◽  
pp. 11612
Author(s):  
Eun-Joo Kim ◽  
Ji-Young Lim ◽  
Geun-Myun Kim ◽  
Seong-Kwang Kim
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Nursing Students ◽  
Network Analysis ◽  
Group Dynamics ◽  
Future Research ◽  
Subjective Happiness ◽  
Cross Sectional Survey ◽  
Cross Sectional ◽  
High Level

Improving nursing students’ subjective happiness is germane for efficiency in the nursing profession. This study examined the subjective happiness of nursing students by applying social network analysis (SNA) and developing a strategy to improve the subjective happiness of nursing. The study adopted a cross sectional survey to measure subjective happiness and social network of 222 nursing students. The results revealed that the centralization index, which is a measure of intragroup interactions from the perspective of an entire network, was higher in the senior year compared with the junior year. Additionally, the indegree, outdegree, and centrality of the social network of students with a high level of subjective happiness were all found to be high. This result suggests that subjective happiness is not just an individual’s psychological perception, but can also be expressed more deeply depending on the subject’s social relationships. Based on the study’s results, to strengthen self-efficacy and resilience, it is necessary to utilize strategies that activate group dynamics, such as team activities, to improve subjective happiness. The findings can serve as basic data for future research focused on improving nursing students’ subjective happiness by consolidating team-learning social networks through a standardized program approach within a curriculum or extracurricular programs.

Inter-provincial correlations of agricultural GHG emissions in China based on social network analysis methods

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jiansheng Qu ◽  
Jinyu Han ◽  
Lina Liu ◽  
Li Xu ◽  
Hengji Li ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Temporal Trends ◽  
Ghg Emissions ◽  
Policy Implications ◽  
Content Type ◽  
Ghg Reduction ◽  
And Cluster Analysis ◽  
Practical Implications

PurposeThe purpose of this paper is to explore the heterogeneity and correlations of agricultural greenhouse gas (GHG) emissions among provinces in China, and then policy implications are proposed.Design/methodology/approachAfter agricultural GHG accounting and a pre-analysis of inter-provincial heterogeneity, improved gravity model and the Social Network Analysis (SNA) methods are introduced to construct the network, being carried out from three aspects of the whole network, individual provincial characteristics and cluster analysis.Findings(1) There are significant regional variations in agricultural GHG scale among provinces owing to the layout of agricultural production, and the temporal trends show that the direction and speed of agricultural GHG scale change vary among provinces; (2) In terms of inter-provincial correlations, there exists a complex spatial network of agricultural GHG among provinces, which tends to be more complex, intensive and stable, while the status of the provinces in the network also has gradually become more balanced. All provinces played their respective roles in the four clusters of the network with agricultural layout and comparative advantages, and the distribution has continuously optimized.Practical implicationsThe inter-provincial network characteristics of agricultural GHG emissions and its evolution have practical implications for differentiated and coordinated agricultural GHG reduction policies at the provincial levels.Originality/valueThis paper innovatively study inter-provincial agricultural GHG correlations in China with the SNA methods used to study economic and social connections in the past. There is some originality in the introduction of network theory and application of the SNA methods, which can provide some reference for researches in similar fields.

scholarly journals Inter-player variability in game patterns in high-level women's volleyball: A study with Outside Hitters (Near vs. Away) using Social Network Analysis. [Variabilidad entre jugadores en los patrones de juego en el voleibol femenino de alto nivel: Un estudio con bateadores externos (Cerca versus Lejos) usando Análisis de Redes Sociales].

2021 ◽  
Vol 17 (65) ◽  
pp. 234-250
Author(s):  
João Bernardo Martins ◽  
◽  
Isabel Mesquita ◽  
Ademilson Mendes ◽  
Letícia Santos ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Team Sports ◽  
Eigenvector Centrality ◽  
Redes Sociales ◽  
Functional Roles ◽  
High Level ◽  
Women's Volleyball ◽  
After Error

A wide body of research on team sports has focused on positional status based differences, providing information on inter-player variability according to the functional roles within the game. However, research addressing inter-player variability within the same positional/function status is scarce. The present article presents an analysis of inter-player variability within the same positional status during critical moments, in high-level women's volleyball, using Social Network Analysis. Attack actions of the outside hitters near (OHN) and away (OHA) from the setter were analysed in ten matches from the 2019 Volleyball Nations League Finals (268 plays). Two independent Eigenvector Centrality networks were created, one for OHN and another for OHA. Main results: (a) in side-out with ideal setting conditions, the OHA used more tips and exploration of the block than the OHN; under non-ideal setting conditions, the OHN had slower attack tempos than the OHA; (b) OHA used tip and directed attacks after error situations while OHN was typically not requested after error situations; (c) in transition, OHN typically attacked after having performed a previous action, performing a dual task within each ball possession, while OHA only attacked when there was no prior action; (d) there were also inter-positional similarities, with both OHN and OHA preferring a strong attack in ideal conditions during KI and KIV, and slower tempos in transition in non-ideal conditions. Conclusions: Even within the same positional status, there seems to be subtle, but relevant inter-player variability. Consequently, coaches should devote careful attention when assigning players to positional.

Spatiotemporal Network Analysis and Visualization

2015 ◽  
Vol 6 (2) ◽  
pp. 77-97 ◽  
Author(s):  
Judith Gelernter ◽  
Kathleen M. Carley
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Third Party ◽  
Analysis Software ◽  
Time Intervals ◽  
External Resources ◽  
Newspaper Articles

Spatiotemporal social network analysis shows relationships among people at a particular time and location. This paper presents an algorithm that mines text for person and location words and creates connections among words. It shows how this algorithm output, when chunked by time intervals, may be visualized by third-party social network analysis software in the form of standard network pin diagrams or geographic maps. Its data sample comes from newspaper articles concerning the 2006 Darfur crisis in Sudan. Given an immense data sample, it would be possible to use the algorithm to detect trends that would predict the next geographic center(s) of influence and types of actors (foreign dignitaries or domestic leaders, for example). This algorithm should be widely generalizable to many text domains as long as the external resources are modified accordingly.

Spatiotemporal Network Analysis and Visualization

2016 ◽  
pp. 373-395
Author(s):  
Judith Gelernter ◽  
Kathleen M. Carley
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Third Party ◽  
Analysis Software ◽  
Time Intervals ◽  
External Resources ◽  
Newspaper Articles

Spatiotemporal social network analysis shows relationships among people at a particular time and location. This paper presents an algorithm that mines text for person and location words and creates connections among words. It shows how this algorithm output, when chunked by time intervals, may be visualized by third-party social network analysis software in the form of standard network pin diagrams or geographic maps. Its data sample comes from newspaper articles concerning the 2006 Darfur crisis in Sudan. Given an immense data sample, it would be possible to use the algorithm to detect trends that would predict the next geographic center(s) of influence and types of actors (foreign dignitaries or domestic leaders, for example). This algorithm should be widely generalizable to many text domains as long as the external resources are modified accordingly.

Using social network analysis to assess climate change professionals’ communications in Iran

2021 ◽  
Keyword(s):  
Climate Change ◽  
Grounded Theory ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Third Party ◽  
Structured Interviews ◽  
Adaptation To Climate Change ◽  
Adaptation Measures ◽  
Cooperative Relationship

Abstract Increased cooperation of an interdisciplinary group of climate change professionals as a social network can play a crucial role in adaptation to climate change. To investigate this relationship at the country-scale, this study uses a case study in Iran in order to 1) measure the cooperative relationship among climate change professionals using the network analysis approach, and; 2) analyze the potential of the network in promoting adaptation measures based on sustainable development. Social network analysis, which is both a quantitative and qualitative method of grounded theory was used to analyze the data. Data collection was performed using two questionnaires including network analysis and a survey, as well as a number of semi-structured interviews with the climate change professionals. The data was collected from climate change professionals including a sample of 55 individuals who were surveyed as a complete network. The network relationship results have been analyzed using different tests at three (micro, macro and the interactions between the two) levels. The results have shown that the connectedness of the network is 23.7%, with 42.4% mutual links. The transitivity rate in the network is 51.39%, which determines the possibility of each professional communicating with a third party. According to the normalized degree index, 34.29% of the cases are in contact with other researchers in the network and 53.15% received a connection from others. Grounded theory analysis showed that five core categories including social capital, managerial factors, research, relations, and coordination affected the quality and utility of Iranian climate change professionals’ network.

Walking the dog: exploration of the contact networks between dogs in a community

2008 ◽  
Vol 137 (8) ◽  
pp. 1169-1178 ◽  
Author(s):  
C. WESTGARTH ◽  
R. M. GASKELL ◽  
G. L. PINCHBECK ◽  
J. W. S. BRADSHAW ◽  
S. DAWSON ◽  
...  
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Public Space ◽  
Contact Networks ◽  
Minimum Path ◽  
Potential Contact ◽  
High Connectivity ◽  
Path Lengths ◽  
High Level

SUMMARYThis study uses social network analysis to investigate potential contact among 214 dog-owning households in a UK community through their utilization of public space during walking. We identified a high level of potential contact between dog-owning households; most households walked their dogs in only a few areas but a small number visited many. Highly connected households were more likely to have multiple dogs, walk their dogs off lead, and own Working, Pastoral or some Terrier types. Similarly, most areas were only visited by a few households but a few were visited by many. Despite identification of subgroups of households and locations, we demonstrated high connectivity between dog-owning households, with minimum path lengths of two ‘steps’ (household–area–household, 74%) or four ‘steps’ (via two areas, 26%).

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