INSNA Sunbelt 2025で発表を行います
2025年6月23日（月）～ 29日（日）に開催されるINSNA Sunbelt 2025（パリ・ソルボンヌ大学）で，以下の発表を行います。
【OS-150: Modeling Network Dynamics 2】
- Tasuku Igarashi, Johan Koskinen, Colin Gallagher, Conrad Chan, David Liptai (2025). More nominations, less reciprocation: Modeling an “overchoosing” phenomenon in large social networks (6月28日 11:00~11:20) Link
Social network researchers often assume that mutual nominations between actors are more likely to occur than one-sided nominations. However, this assumption does not always hold, particularly in large social networks. Actors who nominate many others often do not achieve complete reciprocation from all their nominees. In this presentation, we introduce a new parameter termed “overchoosing,” which integrates reciprocity and outdegree popularity effects as their product. This parameter captures an endogenous tie-formation process not adequately represented by existing network configurations. We hypothesize a negative estimate for the overchoosing parameter, indicating that the greater the number of outgoing nominations by an actor, the lower the likelihood that each nomination will be reciprocated. To test this hypothesis, we implemented the overchoosing parameter within stochastic actor-oriented models (SAOM). Analyses of secondary school friendship networks (N > 1000, two waves) demonstrated that the model including the overchoosing parameter provided a better fit to observed data compared to a model without it, as evaluated by the triad census goodness-of-fit indices—particularly for the triadic out-star without reciprocation (021D). We also present and discuss findings from additional analyses of online social networks and bitcoin trust networks (Ns > 500, number of waves > 100) by Bayesian SAOM optimized for parallel computation on supercomputers (Chan et al., 2022). These insights help refine our understanding of how reciprocal relationships form or dissolve in larger social networks.
