Utilising qualitative data for social network analysis in disaster research: opportunities, challenges, and an illustration.

An abundance of unstructured and loosely structured data on disasters exists and can be analysed using network methods. This paper overviews the use of qualitative data in quantitative social network analysis in disaster research. It discusses two types of networks, each with a relevant major topic in disaster research-that is, (i) whole network approaches to emergency management networks and (ii) personal network approaches to the social support of survivors-and four usable forms of qualitative data. This paper explains five opportunities afforded by these approaches, revolving around their flexibility and ability to account for complex network structures. Next, it presents an empirical illustration that extends the authors' previous work examining the sources and the types of support and barrier experienced by households during long-term recovery from Hurricane (Superstorm) Sandy (2012), wherein quantitative social network analysis was applied to two qualitative datasets. The paper discusses three challenges associated with these approaches, related to the samples, coding, and bias.

Examining Variation in Emotional Distress among Individuals with a Cancer Diagnosis.

This study examined whether emotional distress among U.S. adults diagnosed with cancer was influenced by death rates, survival rates, and new cases based on cancer type and individual-level variables (health efficacy, perceived health, and use of information and communication technologies and social media for health-related reasons). Health Information National Trends Survey 5 data from cycle 1 and cycle 2 were used to examine emotional distress among individuals who had experienced 1 of 17 different types of cancer diagnoses. A multilevel model and follow-up one-way ANOVA indicated a small statistically significant difference in emotional distress across cancer types. To investigate the influence of individual-level variables on emotional distress, a hierarchical regression analysis indicated that, after controlling for perceived health and health efficacy, using social media in a greater number of health-related ways significantly predicted greater emotional distress, while using information and communication technologies in a greater number of health-related ways did not.