Towards a general method to classify personal network structures
González-Casado, Miguel A. (Universidad Carlos III. Departamento de Matemáticas)
Gonzales, Gladis (Loyola University Andalusia)
Molina, José Luis (Universitat Autònoma de Barcelona. Departament d'Antropologia Social i Cultural)
Sánchez, Angel (Universidad Carlos III. Departamento de Matemáticas)

Data:	2024
Descripció:	14 pàg.
Resum:	In this study, we present a method to uncover the fundamental dimensions of structural variability in Personal Networks (PNs) and develop a classification solely based on these structural properties. We address the limitations of previous literature and lay the foundation for a rigorous methodology to construct a Structural Typology of PNs. We test our method with a dataset of nearly 8,000 PNs belonging to high school students. We find that the structural variability of these PNs can be described in terms of six basic dimensions encompassing community and cohesive subgroup structure, as well as levels of cohesion, hierarchy, and centralization. Our method allows us to categorize these PNs into eight types and to interpret them structurally. We assess the robustness and generality of our methodology by comparing with previous results on structural typologies. To encourage its adoption, its improvement by others, and to support future research, we provide a publicly available Python class, enabling researchers to utilize our method and test the universality of our results.
Ajuts:	Agencia Estatal de Investigación PID2022-141802NB-I00 Ministerio de Economía y Competitividad PID2021-126892NB100
Nota:	Altres ajuts: Agencia Andaluza de Cooperación Internacional para el Desarrollo (AACID-0I008/2020, AACID-2021UI004)
Drets:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades.
Llengua:	Anglès
Document:	Article ; recerca ; Versió publicada
Matèria:	Clustering ; Dimensionality reduction ; Personal networks ; Social networks analysis ; Structural typology
Publicat a:	Social networks, Vol. 78 (2024) , p. 265-278, ISSN 1879-2111

DOI: 10.1016/j.socnet.2024.03.004

14 p, 1.8 MB

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