ArticleScientific reports2024
An empirical study on social network analysis for small residential communities in Gangwon State, South Korea.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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Who cites it
2 citing papers in PubMed.
- Community evolution prediction based on feature change patterns in social networks.Scientific reports · 2025Article
- Temporal social network modeling of mobile connectivity data with graph neural networks.PloS one · 2025Article
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Authors and funding
8 authors.
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Abstract
Social Network Analysis (SNA) provides a dynamic framework for examining interactions and connections within networks, elucidating how these relationships impact behaviors and outcomes. This study targeted small residential communities in Gangwon State, South Korea, to explore network formation theories and derive strategies for enhancing health promotion services in rural communities. Conducted in 12 small residential areas, the survey led to a network categorization model distinguishing networks as formal, informal, or non-existent. Key findings demonstrated that demographic and socio-economic factors, specifically age, income, living environment, leisure activities, and education level, significantly influence network formation. Importantly, age, environmental conditions, satisfaction with public transportation, and walking frequency were closely associated with the evolution of formal networks. These results highlight the importance of early community network assessments, which must consider distinct network traits to develop effective health promotion models. Utilizing SNA early in the assessment process can improve understanding of network dynamics and optimize the effectiveness of health interventions.
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