An empirical study on social network analysis for small residential communities in Gangwon State, South Korea

• Published in: Scientific reports Vol. 14; no. 1; p. 11648
• Main Authors: Jeong, Dae-hyun, Lee, Sang-Kyu, Ahn, Moo-Eob, Kim, Sang Mi, Ryu, Ohk-Hyun, Park, Kyung Suk, Shin, Se Gye, Han, Jae Hyun
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 22.05.2024; Nature Publishing Group; Nature Portfolio
• Subjects: 692/308; 692/700; Adult; Aged; Community network; Economic factors; Environmental conditions; Female; Health Promotion; Humanities and Social Sciences; Humans; Male; Middle Aged; multidisciplinary; Public transportation; Republic of Korea; Residence Characteristics; Residential areas; Rural areas; Rural Population; Science; Science (multidisciplinary); Social Network Analysis; Social Networking; Social networks; Social organization; Social Support; Socioeconomic Factors; Socioeconomics; Young Adult; Republic of Korea; South Korea; Health promotion; Community network; Social network analysis
• ISSN: 2045-2322; 2045-2322
• DOI: 10.1038/s41598-024-62371-x

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.