scholarly journals THE IMPORTANCE OF SOCIAL NETWORK CONNECTION IN VOCATIONAL EDUCATION: AMIGURUMI HANDCRAFT EXPANSION IN MARDIN

2022 ◽  
Vol 2 (1) ◽  
pp. 27-35
Author(s):  
Mustafa Şeref AKIN
Keyword(s):  
Social Network ◽  
Vocational Education ◽  
Network Connection

scholarly journals The Relation between Organizational Network Distance and Knowledge Transfer Based on Social Network Analysis Method

2017 ◽  
Vol 12 (06) ◽  
pp. 171
Author(s):  
Muyun Sun
Keyword(s):  
Social Network ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Knowledge Transfer ◽  
Analysis Method ◽  
Network Distance ◽  
Organizational Network ◽  
Network Connection ◽  
Knowledge Growth ◽  
Negative Effect

As a means to maintain competitive advantages of organizations, knowledge transfer has attracted more and more attention in the academic circle. In this paper, the concept of network distance is introduced on the basis of social network analysis method, and the influence of network distance between organizations in social network on knowledge transfer is studied. Moreover, analogue simulation is conducted by utilizing 10 innovative enterprises in Shanghai Withub Hi-Tech Center. According to the researches, firstly, knowledge growth rate of the entire network tends to increase at first and then becomes stable as time passes. In this process, knowledge difference level among various organizations continues to decline and tends to be stable finally. Secondly, network distance has a negative effect on knowledge transfer. According to the simulation results, organizations need to continuously improve their knowledge absorption ability, to change the network connection mode, and to form a close network with other organizations.

scholarly journals The circulation analysis of substandard foods in China based on GIS and social network analysis

PLoS ONE ◽  
2021 ◽  
Vol 16 (3) ◽  
pp. e0248037
Author(s):  
Yakun He ◽  
Jiadong Jiang ◽  
Shuo Li
Keyword(s):  
Social Network ◽  
Food Safety ◽  
Social Network Analysis ◽  
Network Analysis ◽  
Safety Issues ◽  
Network Connection ◽  
Sampling Inspection ◽  
Safety Risks ◽  
Province Level ◽  
Circulation Characteristics

In China, the majority of food enterprises are small-sized and medium-sized. While the supervision costs are high, food safety issues are still emerging. Food circulation is an indispensable part in the entire food chain. At present, there are few studies on the regional spread of food safety risks in the circulation field from a macro perspective. This study combines GIS and social network analysis methods to deeply explore the regional circulation characteristics of substandard foods. First, we crawl the dataset of Food Safety Sampling Inspection Result Query System. Then we obtain the geographical locations of the manufacturers and distributors by GIS. Finally, we construct the province-level and city-level substandard foods’ circulation networks, and employ social network analysis to target key cities and paths. The experimental results show that the circulations of substandard foods are characterized by dense province-level network and sparse city-level network, and they are mostly local and short-distance trafficking. 361 cities are divided into 13 city clusters considering the network connection characteristics. Chongqing, Beijing, Zhengzhou, and Changsha are identified as key cities by all measurement indicators, and at least four indicators can identify Shanghai and Wuhan. These cities have the highest priority for combating substandard foods’ circulation networks.

The social network

2013 ◽  
Vol 44 (2) ◽  
pp. 22
Author(s):  
ALAN ROCKOFF
Keyword(s):  
Social Network ◽  
The Social

Abstract #1249: Novel Use of Physician Social Network Data to Map the Gap in the Endocrinology Workforce

2015 ◽  
Vol 21 ◽  
pp. 301
Author(s):  
Armand Krikorian ◽  
Lily Peng ◽  
Zubair Ilyas ◽  
Joumana Chaiban
Keyword(s):  
Social Network ◽  
Network Data ◽  
Social Network Data

Correlating Personality and Actual Phone Usage

2014 ◽  
Vol 35 (3) ◽  
pp. 158-165 ◽  
Author(s):  
Christian Montag ◽  
Konrad Błaszkiewicz ◽  
Bernd Lachmann ◽  
Ionut Andone ◽  
Rayna Sariyska ◽  
...  
Keyword(s):  
Big Data ◽  
Social Network ◽  
Mobile Phone ◽  
Mobile Phones ◽  
Self Report ◽  
Psychological Variables ◽  
New Approach ◽  
Report Data ◽  
Self Report Data ◽  
Voice Calls

In the present study we link self-report-data on personality to behavior recorded on the mobile phone. This new approach from Psychoinformatics collects data from humans in everyday life. It demonstrates the fruitful collaboration between psychology and computer science, combining Big Data with psychological variables. Given the large number of variables, which can be tracked on a smartphone, the present study focuses on the traditional features of mobile phones – namely incoming and outgoing calls and SMS. We observed N = 49 participants with respect to the telephone/SMS usage via our custom developed mobile phone app for 5 weeks. Extraversion was positively associated with nearly all related telephone call variables. In particular, Extraverts directly reach out to their social network via voice calls.

Extraverts Have Larger Social Network Layers

2011 ◽  
Vol 32 (3) ◽  
pp. 161-169 ◽  
Author(s):  
Thomas V. Pollet ◽  
Sam G. B. Roberts ◽  
Robin I. M. Dunbar
Keyword(s):  
Social Network ◽  
Social Relationships ◽  
Outer Layer ◽  
Network Size ◽  
Emotional Intensity ◽  
Emotional Closeness ◽  
Network Layer ◽  
Network Layers ◽  
Social Network Size

Previous studies showed that extraversion influences social network size. However, it is unclear how extraversion affects the size of different layers of the network, and how extraversion relates to the emotional intensity of social relationships. We examined the relationships between extraversion, network size, and emotional closeness for 117 individuals. The results demonstrated that extraverts had larger networks at every layer (support clique, sympathy group, outer layer). The results were robust and were not attributable to potential confounds such as sex, though they were modest in size (raw correlations between extraversion and size of network layer, .20 < r < .23). However, extraverts were not emotionally closer to individuals in their network, even after controlling for network size. These results highlight the importance of considering not just social network size in relation to personality, but also the quality of relationships with network members.

The Multilevel p2 Model

Methodology ◽  
2006 ◽  
Vol 2 (1) ◽  
pp. 42-47 ◽  
Author(s):  
Bonne J. H. Zijlstra ◽  
Marijtje A. J. van Duijn ◽  
Tom A. B. Snijders
Keyword(s):  
Social Network ◽  
Network Data ◽  
Mcmc Algorithm ◽  
Independent Observation ◽  
Single Observation ◽  
Multiple Networks ◽  
Social Network Data ◽  
Multiple Observations ◽  
Practical Support ◽  
The Social

The p 2 model is a random effects model with covariates for the analysis of binary directed social network data coming from a single observation of a social network. Here, a multilevel variant of the p 2 model is proposed for the case of multiple observations of social networks, for example, in a sample of schools. The multilevel p 2 model defines an identical p 2 model for each independent observation of the social network, where parameters are allowed to vary across the multiple networks. The multilevel p 2 model is estimated with a Bayesian Markov Chain Monte Carlo (MCMC) algorithm that was implemented in free software for the statistical analysis of complete social network data, called StOCNET. The new model is illustrated with a study on the received practical support by Dutch high school pupils of different ethnic backgrounds.

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