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Network-based study of segregation and social capital in the Netherlands using population-scale social network data derived from official population registers

November 16 , 08:00 17:00 UTC+2

Conference talk by Yuliia Kazmina at the Dutch Demography Day 2022.

Using population-scale social network data derived from official population registers, we propose a network-based study of segregation and social capital in the Netherlands. 

Segregation is a widely studied issue traditionally explored from the point of the spatial distribution of different groups as defined by any individual attribute such as race, religion, social class, etc. Nevertheless, we argue that the issues of persistent segregation, specifically socio-economic segregation, are networked phenomena and should be studied as such. We measure to what extent Dutch residents in different municipalities are exposed to individuals of different socio-economic statuses in diverse social contexts and what social contexts provide diverse social contact opportunities with respect to the socio-economic status and, on the contrary, what social contexts play a role of socio-economic bubbles. Our findings suggest great heterogeneity in socio-economic assortativity between different social contexts as well as different municipalities. 

Social capital can be seen as the value and resources found in social structures which enable collective action. It is most often measured indirectly based on theoretical argumentation using data on its expected outcomes, such as civic participation or volunteering rates. We determine the relationship between network measures of bridging and bonding social capital and volunteering rates. The results of the regression analyses show a significant relation between rates of social bonding and social capital. Network measures related to social bridging have a significant but weaker and negative impact on social capital. This suggests that the type of social capital must be carefully considered when attempting to measure social capital using networks. Our work presents the first major steps for the measurement of social capital using population-scale network data. The findings can be valuable to anyone measuring social capital in networks, paving the way for informed decision-making aimed at increasing social capital of, for example, minority groups.