Vörös, András and Boda, Zsófia and Elmer, Timon and Hoffman, Marion and Mepham, Kieran and Raabe, Isabel J and Stadtfeld, Christoph (2021) The Swiss StudentLife Study: Investigating the emergence of an undergraduate community through dynamic, multidimensional social network data. Social Networks, 65. pp. 71-84. DOI https://doi.org/10.1016/j.socnet.2020.11.006
Vörös, András and Boda, Zsófia and Elmer, Timon and Hoffman, Marion and Mepham, Kieran and Raabe, Isabel J and Stadtfeld, Christoph (2021) The Swiss StudentLife Study: Investigating the emergence of an undergraduate community through dynamic, multidimensional social network data. Social Networks, 65. pp. 71-84. DOI https://doi.org/10.1016/j.socnet.2020.11.006
Vörös, András and Boda, Zsófia and Elmer, Timon and Hoffman, Marion and Mepham, Kieran and Raabe, Isabel J and Stadtfeld, Christoph (2021) The Swiss StudentLife Study: Investigating the emergence of an undergraduate community through dynamic, multidimensional social network data. Social Networks, 65. pp. 71-84. DOI https://doi.org/10.1016/j.socnet.2020.11.006
Abstract
The Swiss StudentLife Study (SSL Study) is a longitudinal social network data collection conducted in three undergraduate student cohorts (N1 = 226, N2 = 261, N3 = 660) in 2016−2019. The main goal of the study was to understand the emergence of informal student communities and their effects on different individual outcomes, such as well-being, motivation, and academic success. To this end, multiple dimensions of social ties were assessed, combining computer-based surveys, social sensors, social media data, and field experiments. The dynamics of these social networks were measured on various time scales. In this paper, we present the design and data collection strategy of the SSL Study. We discuss practical challenges and solutions related to the data collection in four areas that were key to the success of our project: study design, research ethics, communication, and population definition.
Item Type: | Article |
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Uncontrolled Keywords: | Dynamic networks; Multidimensional networks; Education; Network data collection |
Divisions: | Faculty of Social Sciences Faculty of Social Sciences > Sociology and Criminology, Department of |
SWORD Depositor: | Unnamed user with email elements@essex.ac.uk |
Depositing User: | Unnamed user with email elements@essex.ac.uk |
Date Deposited: | 07 Feb 2025 15:06 |
Last Modified: | 07 Feb 2025 15:06 |
URI: | http://repository.essex.ac.uk/id/eprint/40253 |
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