Analysing the geography of personal networks beyond the question of distance

Claire Bidart, Marion Maisonobe, Gil Viry

Contact: marion.maisonobe@cnrs.fr

Social ties and social networks develop in and across geographical spaces. Network scholars have shown that individuals, families, scientists, firms, diasporas, activists, etc. can develop their relationships over large distances while places and spatial proximity continue to strongly structure social networks. Yet, social network research has not fully taken up issues of space and place. The role of space in the formation and maintenance of ties has often been analysed through the lens of physical distance – usually as something ‘from the outside’ to overcome – rather than as an inherent characteristic of relationships and networks. Mapping and analysing personal networks in the geographical space presents opportunities but also challenges, both conceptually and methodologically. In this paper, we present a novel approach for analysing personal networks based on their geographical scope and the distribution of network members across employment areas, regions and countries. While the ego-alter distance is a central characteristic for understanding their relationship, it is a rough indicator for investigating how networks and space interweave. In order to capture the diversity of spatial patterns of personal networks, including alters’ clustering in some places but also their geographical scattering, we need indicators that reflect social network complexity. By combining the disciplines of sociology and human geography and the qualitative and quantitative network analysis, we seek to develop a method that accounts for the spatial patterns of networks with greater relevance and can be replicated across various databases. Our data come from two different egocentric network datasets: (1) the Panel of Caen (France), which is a qualitative follow-up study based on activity-focused name generators capturing large networks (87 Egos along 5 survey waves with a mean size of 37 alters); (2) the nationally representative 2013 MosaiCH-ISSP survey including the ego-centric family networks of 666 adults living in Switzerland. Personal networks were based on a unique name generator asking respondents to self-define their meaningful family members. Four types of relationships were measured: emotional support, material support, influence and conflict. Using these two datasets, we identify the main geographical patterns of personal networks and examine how these patterns relate to important characteristics of the individuals and networks. We discuss the significance and limitations of our approach to integrate geographical information into the analysis of personal networks.

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