https://doi.org/10.1140/epjds/s13688-023-00436-z
Commentary
Studying social networks in the age of computational social science
Department of Humanities and Social Sciences, ETH Zurich, Weinbergstrasse 109, 8092, Zurich, Switzerland
Received:
8
January
2023
Accepted:
30
November
2023
Published online:
19
December
2023
Social and behavioral sciences now stand at a critical juncture. The emergence of Computational Social Science has significantly changed how social networks are studied. In his keynote at IC2S2 2021, Lehmann presented a series of research based on the Copenhagen Network Study and pointed out an important insight that has mostly gone unnoticed for many network science practitioners: the data generation process — in particular, how data is aggregated over time and the medium through which social interactions occur — could shape the structure of networks that researchers observe. Situating the keynote in the broader field of CSS, this commentary expands on its relevance for the shared challenges and ongoing development of CSS.
Key words: Computational social science (CSS) / Dynamic networks / Data aggregation
© The Author(s) 2023
Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.