Paper on VINA: A new interface to collect social network data

Discover our paper published by Social Networks on VINA: A new engaging and ethical interface to collect social network data: Tom Nijs, Tobias H. Stark, Zsófia Boda, Introducing VINA: An engaging and ethically responsible interface to collect social network data including cognitive social structures on smartphones, Social Networks, Volume 87, 2026, Pages 92-102, ISSN 0378-8733, https://doi.org/10.1016/j.socnet.2026.06.005.

Abstract

We introduce VINA (Visual Interface for Network Assessment), an open-source software tool designed to collect quantitative social network data in an intuitive, engaging, and ethically responsible manner. VINA is developed to remain clear and scalable on small screens, regardless of the number of reported social relations. As a result, it is the first graphical interface that allows researchers to collect cognitive social structures (i.e., perceptions of alter-alter relationships in complete networks) on smartphones. VINA also enables researchers to dynamically integrate participants’ self-reported names into the surveys of other participants in real time, eliminating the need to gather name lists prior to informed consent and thereby addressing key ethical concerns. We outline the motivation behind VINA, describe its development process, and highlight its benefits and novel features for social network research. Using large-scale school data collected with VINA (N = 1341), we further examine how design choices influence data quality. Specifically, we assess how completion time varies with network size, how alphabetical name order in name generators affects peer nominations, and the extent to which cognitive social structures correspond meaningfully to self-reported networks. We conclude by discussing practical lessons from this first large-scale deployment, along with directions for future development. Overall, VINA has the potential to make the collection of complete network data more convenient for researchers and more engaging for participants. Moreover, we believe VINA will significantly reduce the practical barriers that have long limited the collection of cognitive social structure data.