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Structure in personal networks: Constructing and comparing typologies

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  • Vacca, Raffaele

Abstract

A recurrent finding in personal network research is that individual and social outcomes are influenced not just by the kind of people one knows, but also by how those people are connected to each other. Personal network structure – the way in which one’s personal contacts know and interact with each other – reflects broader trends in social organization and personal communities, and shapes patterns of social capital, support, and isolation. This article proposes a method to identify typologies of structure in large collections of personal networks. The method is applied to six datasets collected in widely different circumstances and using various survey instruments. It is then compared with another recently introduced method to extract typologies of egocentric network structure. Findings show that personal network structure can be effectively summarized using just three measures of cohesive subgroup characteristics. Structural typologies can then be identified by applying standard cluster analysis techniques to the three variables. Both methods considered in the article capture significant variation in network structures, but they also show substantial levels of disagreement and cross-classification. I discuss similarities and differences between the methods, and potential applications of the proposed typologies to substantive research on personal communities, social support, and social capital.

Suggested Citation

  • Vacca, Raffaele, 2020. "Structure in personal networks: Constructing and comparing typologies," Network Science, Cambridge University Press, vol. 8(2), pages 142-167, June.
  • Handle: RePEc:cup:netsci:v:8:y:2020:i:2:p:142-167_2
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    Cited by:

    1. Claire Bidart & Rym Ibrahim, 2023. "How to Locate Resources in the Personal Networks along the Entrepreneurial Processes? Follow-up of a Nascent Digital Nomad Entrepreneur," Post-Print hal-04383505, HAL.
    2. Olha Semenda & Yuliia Sokolova & Olena Korovina & Oleksandra Bratko & Iryna Polishchuk, 2024. "Using Social Media Analysis to Improve E-commerce Marketing Strategies," International Review of Management and Marketing, Econjournals, vol. 14(4), pages 61-71, July.
    3. Elvira Pelle & Roberta Pappadà, 2021. "A clustering procedure for mixed-type data to explore ego network typologies: an application to elderly people living alone in Italy," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(5), pages 1507-1533, December.
    4. González-Casado, Miguel A. & Molina, Jose Luis & Sánchez, Angel, 2023. "Towards a General Typology of Personal Network Structures," SocArXiv 23efd, Center for Open Science.
    5. Danielle Lee, 2023. "Bibliometric analysis of Asian ‘language and linguistics’ research: A case of 13 countries," Palgrave Communications, Palgrave Macmillan, vol. 10(1), pages 1-23, December.
    6. Bilecen, Başak & Vacca, Raffaele, 2021. "The isolation paradox: A comparative study of social support and health across migrant generations in the U.S," Social Science & Medicine, Elsevier, vol. 283(C).

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