The aims: (i) analyze connectivity between subgroups of university students, (ii) assess which bridges of relational contacts are essential for connecting or disconnecting subgroups and (iii) to explore the similarities between the attributes of the subgroup nodes in relation to the pandemic context. During the COVID-19 pandemic, young university students have experienced significant changes in their relationships, especially in the halls of residence. Previous research has shown the importance of relationship structure in contagion processes. However, there is a lack of studies in the university setting, where students live closely together. The case study methodology was applied to carry out a descriptive study. The participation consisted of 43 university students living in the same hall of residence. Social network analysis has been applied for data analysis. Factions and Girvan–Newman algorithms have been applied to detect the existing cohesive subgroups. The UCINET tool was used for the calculation of the SNA measure. A visualization of the global network will be carried out using Gephi software. After applying the Girvan–Newman and Factions, in both cases it was found that the best division into subgroups was the one that divided the network into 4 subgroups. There is high degree of cohesion within the subgroups and a low cohesion between them. The relationship between subgroup membership and gender was significant. The degree of COVID-19 infection is related to the degree of clustering between the students. College students form subgroups in their residence. Social network analysis facilitates an understanding of structural behavior during the pandemic. The study provides evidence on the importance of gender, race and the building where they live in creating network structures that favor, or not, contagion during a pandemic.
【저자키워드】 public health, Psychology and behaviour, 【초록키워드】 Structure, pandemic, COVID-19 pandemic, Gender, Participation, COVID-19 infection, Algorithm, Research, Data analysis, Clustering, Visualization, network, case study, methodology, university students, social network analysis, Evidence, Contact, similarity, Contagion, best, social network, subgroup, subgroups, favor, residence, similarities, calculation, college, aims, attributes, connectivity, building, cohesion, attribute, Gephi software, shown, significant changes in, was used, detect, lack, carried, applied, facilitate, provide, creating, 【제목키워드】 network analysis, identification, subgroup, approach,