Measurement of Social Networks for Innovation within Community Disaster Resilience

Abstract

Disaster risk reduction (DRR) research has long recognised that social networks are a vital source of support during and after a shock. However, the quantification of this social support, primarily through its recognition as social capital, has proven problematic as there is no singular method for its measurement, invalidating the credibility of studies that try to correlate its effects with community disaster resilience. Within the wider resilience field, research that specifically utilises social networks as the focus of analysis is evolving. This paper provides a critical synthesis of how this developing discourse is filtering into community disaster resilience, reviewing empirical case studies from the Global South within DRR that use social network analysis and connectivity measurement. Our analysis of these studies indicates that a robust methodology utilising social network analysis is emerging, which offers opportunity for research cross-comparability. Our review also finds that without this bottom-up mapping, the implementation of top-down preparedness policy and procedures are likely to fail, resulting in the advocation of social network analysis as a critical methodology in future resilience research and policy planning.

A Study on the Job Retention Intention of Nurses Based on Social Support in the COVID-19 Situation

“…Lastly, there are differences in job engagement and job retention intention based on the categories and types of social support. This result is consistent with the research results that state that social support reduces job stress [41] and helps overcome disasters [42]. In addition, research targeted at nurses reports that the level of burnout decreases as social support increases [43].…”

Earthquake preparedness among religious minority groups: the case of the Jewish ultra-Orthodox society in Israel

“…We conducted a special-purpose social survey comprising both open-ended and closed-ended questions, which was distributed throughout the general Jewish ultra-Orthodox public. The questionnaire was based on a reliable and validated questionnaire created by Ya'ar et al (2015), who studied Golan-Agnon, 2020). An ultra-Orthodox neighborhood is defined as a neighborhood where over 50 % of the Jewish population aged 15 or older are ultra-Orthodox (Korach and Choshen, 2020, p. 25).…”

“…This gap can be explained at least in part by religious factors, such as the dominant fatalism embedded in religious and magical beliefs (Audru et al (2013); compare Azim and Islam (2016) in the context of Saudi Arabia). Moreover, some religious communities have minimal exposure to media, which can increase their vulnerability (Ya'ar et al, 2015). However, Gianisa and Le De (2018) showed how religious beliefs can improve disaster preparedness.…”

A Cooperative Interdisciplinary Task Intervention with Undergraduate Nursing and Computer Engineering Students

“…The structural analysis of networks can be applied to various fields of study, such as business relationships [33], tourist travel intentions [34], resilience in disasters [35], and mental health [36]. In the field of education, the context of the present study, SNA has been applied to explore (i) the social influence of ties on adolescents' mental health [37], (ii) the social dynamics of groups in educational camps [38], and (iii) the formation of friendships between students from different ethnic groups [39].…”