@article{0ea390c7b12b4d11b19694195495c90c,
title = "Networks of context: Three-layer socio-cultural mapping for a Verstehende network analysis",
abstract = "What social ties are and how they operate depends on the cultural context constitutive of their meaning. Pursuing an explanatory account for the cultural embeddedness of social ties, we draw on Verstehende sociology and rely on in-depth insight into subjective perceptions developed by social network actors throughout their practice to represent symbolic and material contexts of social ties structurally. We put forward a new mixed data collection and processing approach that ethnographically maps interconnected three-layer socio-cultural networks of individuals, signs, and material objects. Opening cultural contexts to application of formal and statistical techniques, this approach allows for an 'interpretive explanation' of social ties. Illustrating the approach with our own longitudinal study of five European art groups, we discuss the peculiarities of three-layer socio-cultural data collection and processing, the new discoveries enabled, the challenges encountered, the solutions we came up with, and the utility of this approach for conducting 'Verstehende network analysis' in various fields of application.",
keywords = "Cultural context, Mixed method, Network data, Three-layer socio-cultural network, Verstehende network analysis",
author = "Nikita Basov and Darya Kholodova",
note = "Funding Information: This research was supported by Russian Science Foundation (project No. 19-18-00394) in the parts related to conceptual and methodological developments presented in the paper and by Russian Foundation for Basic Research (project No. 18-011-00796) in the parts related to the empirical analysis of creative collectives. Funding Information: We cordially thank Aleksandra Nenko, Anisya Khokhlova, Irina Kretser, Artem Antonyuk, Elena Tsumarova, and Dafne Mutanyola for methodological discussions and related comments on the manuscript. Furthermore, our field study used as an illustration in this article would not be possible without creative collectives which so generously agreed to let us study them. The authors of this paper also express their gratitude to those who participated in field data collection and processing: Anisya Khokhlova, Aleksandra Nenko, Irina Kretser, Dafne Mutanyola, Margarita Kuleva, Artem Antoniuk, Ekaterina Moskaleva, Chiara Pierobon, Liubov Chernysheva, Alexey Evstifeev, Nadezhda Vasilyeva, Anastasia Senicheva, Maria Drozdova, Aleksander Pivovarov, Egor Elnitskiy, Carolin Brune, Silvie Jacobi, Tatyana Adamenko, Alisa Alieva, Alina Kolycheva, and Aleksey Chernorechenskiy. Our special thanks are to Irina Kretser and Margarita Kuleva, the field researchers who helped in selecting illustrations presented in the paper and commented on the initial versions of the manuscript. In addition, this work has benefited from the comments of the participants of the workshop on {\textquoteleft}Empirical Network Data Collection in Social Networks{\textquoteright}, held at University of Oxford in June 2018. Finally, we thank five anonymous reviewers for their insightful comments and the Special Issue Guest Co-Editor Laurin Weissinger for his patient guidance. All typos and mistakes are our own. Publisher Copyright: {\textcopyright} 2021 Elsevier B.V.",
year = "2022",
month = may,
day = "1",
doi = "10.1016/j.socnet.2021.03.003",
language = "English",
volume = "69",
pages = "84--101",
journal = "Social Networks",
issn = "0378-8733",
publisher = "Elsevier BV",
}