Dresden 2026 – wissenschaftliches Programm
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SOE: Fachverband Physik sozio-ökonomischer Systeme
SOE 5: Network Science
SOE 5.2: Vortrag
Dienstag, 10. März 2026, 10:00–10:15, GÖR/0226
Collective decision making with biases - Role of network topology — Yunus Sevinchan1, Petro Sarkanych2, Archili Sakevarashvili1, Yurij Holovatch2,3, and •Pawel Romanczuk1 — 1Institute for Theoretical Biology, Dept. of Biology, Humboldt Universität zu Berlin — 2Yukhnovskii Institute for Condensed Matter Physics of the National Academy of Sciences of Ukraine, Lviv, Ukraine; L4 Collaboration and Doctoral College for the Statistical Physics of Complex Systems, Lviv-Leipzig-Lorraine-Coventry, Europe — 3Complexity Science Hub, Vienna, Austria
The accuracy of collective decision-making in groups depends on a complex interplay of factors, including prior information, biases, social influence, group composition, and the structure of the interaction network. In this work, we study a spin-type model in which interactions are mediated through a social field generated by an agent’s neighbors, allowing for heterogeneous individual preferences. Building on previous results [1], we examine how network topology affects consensus formation. We show that, unlike the Ising model, the social-field model exhibits fundamentally similar behavior on both scale-free and Erdős-Rényi networks, a result that can be attributed to weaker hub-hub interactions. Finally, we investigate the extent to which a strongly biased minority can dominate the collective decision, even in the presence of an oppositely biased majority.
[1] Sarkanych et al, Phys Biol 20 (2023); Sarkanych et al, Cond Matt Phys 27 (2024); Sevinchan et al, Phys Rev Res 7 (2025)
Keywords: collective decision making; opinion formation; networks