Replica allocation policy of cloudy services based on social network properties

2013 ◽  
Vol 33 (8) ◽  
pp. 2143-2146
Author(s):  
Haoyu LUO ◽  
Wanghu CHEN
Keyword(s):  
Social Network ◽  
Allocation Policy ◽  
Replica Allocation ◽  
Network Properties

Athletes as Advocates: Influencing Eating-Disorder Beliefs and Perceptions Through Social Media

2018 ◽  
Vol 11 (4) ◽  
pp. 433-446 ◽  
Author(s):  
Fallon R. Mitchell ◽  
Sara Santarossa ◽  
Sarah J. Woodruff
Keyword(s):  
Social Media ◽  
Eating Disorder ◽  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Text Analysis ◽  
Social Issues ◽  
Penn State ◽  
Network Properties

The present study aimed to explore the interactions and influences that occurred on Twitter after Joey Julius’s (NCAA athlete, Penn State Football) and Mike Marjama’s (MLB player, Seattle Mariners) eating-disorder (ED) diagnoses were revealed. Corresponding with the publicizing of each athlete’s ED, all publicly tagged Twitter media using @joey_julius, Joey Julius, @MMarjama, and Mike Marjama were collected using Netlytic software and analyzed. Text analysis revealed that the conversation was supportive and focused on feelings and size. Social network analysis, based on 5 network properties, showed that Joey Julius invoked a larger conversation but that both athletes’ conversations were single sided. Athlete advocacy on social media should be further explored, as it may contribute to changing societal opinion regarding social issues such as EDs.

scholarly journals Brand influence online: cross-platform social network analysis on the enablement of effective brand communities

2021 ◽  
Author(s):  
Cameron Munro
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Social Networking ◽  
Methodological Approach ◽  
Brand Community ◽  
Brand Communities ◽  
Online Brand Community ◽  
Network Properties ◽  
Cross Platform

This paper aims to provide a systematic methodological approach for online brand community assessment across multiple social networking platforms. Analysis of influential brands was conducted utilizing a social network analysis (SNA) perspective. Brand communities were scored based on network properties and content analysis. Background research provided a framework of recommended community enablement strategies to determine what type of content and approach is most conducive to brand community proliferation. Based on network analysis and on congruency of following academically suggested community enablement triggers and behavioural dimensions, it was determined that the most effective brand at enabling community across all platforms within the study was Yeti Coolers. Instagram was the focal platform providing engaging content to be shared across networks

The association of spatial configuration with social network for elderly in social housing

2017 ◽  
Vol 29 (3) ◽  
pp. 405-416
Author(s):  
Joo Young Kim ◽  
Young Ook Kim
Keyword(s):  
Social Network ◽  
Social Housing ◽  
Elderly Population ◽  
Spatial Configuration ◽  
The Elderly ◽  
Spatial Network ◽  
Apartment Complex ◽  
The Social ◽  
Network Properties

This study aimed to investigate the association of spatial configuration with social interaction for elderly. A social housing in Seoul was selected for the case study. Using space syntax and social network analysis, the association was examined statistically. This research employed an integration indicator which is most closely related to space use pattern. Questionnaire and interview surveys were conducted to illustrate the pattern of social network. Using the collected data, NetMiner was utilized to conduct a quantitative analysis. Degree, closeness and betweenness indicators were employed to measure relationships in these networks and between individuals. The characteristics of the association established by the statistical analysis between spatial network of housing estate and social network of elderly were discussed. Our results show that spatial network properties can explain characteristics of social network. The accessibility of residential spaces for elderly individuals in social housing apartment complex has an effect on the strength of the social network with neighbours. Also, analysis of the spatial configuration accessibility for the elderly population with integration values has illustrated that the result was opposite to the general theory that ‘the locations with high accessibility could foster more interactions’. Our findings have suggested that we can have a better knowledge to foster more social network among elderly by planning improved spatial network.

Resource availability influences global social network properties in Gunnison’s prairie dogs (Cynomys gunnisoni)

Behaviour ◽  
2021 ◽  
pp. 1-18
Author(s):  
Ferenc Jordán ◽  
Bálint Kovács ◽  
Jennifer L. Verdolin
Keyword(s):  
Social Network ◽  
Group Dynamics ◽  
Resource Availability ◽  
Network Size ◽  
Prairie Dogs ◽  
Word Index ◽  
Cynomys Gunnisoni ◽  
Network Connectedness ◽  
Network Properties ◽  
Gunnison's Prairie Dogs

Abstract Increasingly we are discovering that the interactions between individuals within social groups can be quite complex and flexible. Social network analysis offers a toolkit to describe and quantify social structure, the patterns we observe, and evaluate the social and environmental factors that shape group dynamics. Here, we used 14 Gunnison’s prairie dogs networks to evaluate how resource availability and network size influenced four global properties of the networks (centralization, clustering, average path length, small word index). Our results suggest a positive correlation between overall network cohesion and resource availability, such that networks became less centralized and cliquish as biomass/m2 availability decreased. We also discovered that network size modulates the link between social interactions and resource availability and is consistent with a more ‘decentralized’ group. This study highlights the importance of how individuals modify social cohesions and network connectedness as a way to reduce intragroup competition under different ecological conditions.

scholarly journals Associations between social network properties and metabolic syndrome and the mediating effect of physical activity: findings from the Cardiovascular and Metabolic Diseases Etiology Research Center (CMERC) Cohort

2020 ◽  
Vol 8 (1) ◽  
pp. e001272
Author(s):  
Kwanghyun Kim ◽  
Sun Jae Jung ◽  
Jong Min Baek ◽  
Hyeon Woo Yim ◽  
Hyunsuk Jeong ◽  
...  
Keyword(s):  
Physical Activity ◽  
Metabolic Syndrome ◽  
Social Networks ◽  
Social Network ◽  
High Risk ◽  
Alcohol Consumption ◽  
Cigarette Smoking ◽  
Metabolic Diseases ◽  
Community Based ◽  
Network Properties

IntroductionSocial isolation and loneliness are positively associated with metabolic syndrome. However, the mechanisms by which social isolation affects metabolic syndrome are not well understood.Research design and methodsThis study was designed as a cross-sectional study of baseline results from the Cardiovascular and Metabolic Diseases Etiology Research Center (CMERC) Cohort. We included 10 103 participants (8097 community-based low-risk participants, 2006 hospital-based high-risk participants) from the CMERC Cohort. Participants aged 65 years or older were excluded. Multiple imputation by chained equations was applied to impute missing variables. The quantitative properties of social networks were assessed by measuring the ‘size of social networks’; qualitative properties were assessed by measuring the ‘social network closeness’. Metabolic syndrome was defined based on the National Cholesterol Education Program Adult Treatment Panel III criteria. Multivariate logistic regression analyses were conducted to assess association between social network properties and metabolic syndrome. The mediating effects of physical inactiveness, alcohol consumption, cigarette smoking and depressive symptoms were estimated. Age-specific effect sizes were estimated for each subgroup.ResultsA smaller social network was positively associated with higher prevalences of metabolic syndrome in all subgroups, except the high-risk male subgroup. There was no clear association between social network closeness and metabolic syndrome. In community-based participants, an indirect effect through physical activity was detected in both sexes; however, in hospital-based participants, no indirect effects were detected. Cigarette smoking, alcohol consumption and depression did not mediate the association. Age-specific estimates showed that the indirect effect through physical activity had a greater impact in older participants.ConclusionsA smaller social network is positively associated with metabolic syndrome. This trend could be partially explained by physical inactivity, especially in older individuals.

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