Online Social Networks and Subjective Well-being of Older Australians: Network Homogeneity, Social Capital and Negative Interactions
Abstract
This thesis studies the personal networks of older Australians and their associations with subjective well-being (SWB) by focusing on three main characteristics of social networks: homogeneity (connecting with similar people), social capital (access to resources) and negative interactions. Using an innovative purpose-built Facebook application, data on personal networks of 105 Australians aged 50 years and over is collected in two parts. This application collected data on personal networks from Facebook and then loaded them into a visual survey enabling participants to provide information on each relationship (e.g. closeness) and SWB. There are three main findings of this thesis. First, it characterises the personal networks of the sample. In general these networks are loosely-knit, diverse, geographically dispersed and yet, composed of several homogeneous and densely-knit clusters. Further, while there are some negative relationships, they are mostly positive and provide access to a diverse set of resources. Social network scholars have provided a similar view based on limited data collected by conventional methods. This thesis provides a much more detailed characterisation based on the rich data set collected in this research. Second, it provides new insights into the associations between personal networks and SWB. In particular, this study shows that network size is unrelated to SWB, density is negatively associated with SWB, and measures of homogeneity and social capital exhibit either a lack of or a negative association with SWB. Further, a strong detrimental effect of negative interactions on SWB, that has been commonly found in previous research, is not confirmed in this study. Third, this thesis examines whether the above findings are an artefact of the source of personal network data. This view is not supported by the fact that participants’ Facebook personal networks considerably overlap with personal networks in real life. Rather the associations between personal networks and SWB were found to be more related to how personal networks have been constructed than whether they are on Facebook or in real life. It is proposed that previous research has been based on personal networks limited to core network members. Limiting personal networks to close relationships produced a positive association between density and SWB; it is the inclusion of not-close relationships that results in the negative association between density and SWB. The sample used in this study is small and not representative of the target population, thus the findings may not be generalised. However, it provides fresh insights into personal networks and their associations with SWB, by employing a research framework based on social network analysis, utilising advanced methods such as multilevel analysis and benefiting from a rich data set. This thesis provides a basis for future research that is expected to improve our understanding of social networks and their associations with well-being by using more representative samples.
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