Social Networks

Everyday mobility data have become a central resource for studying neighborhoods, yet most research still treats mobility networks as collections of dyadic ties rather than complex systems with higher-order structure. This study investigates whether triadic closure operates causally in neighborhood mobility networks: when two neighborhoods (B and C) increasingly share a common destination (A), do direct mobility flows between B and C strengthen? Using longitudinal smartphone traces from SafeGraph, we construct neighborhood-to-neighborhood mobility networks for U.S. census tracts and define triads in which two “alter” tracts jointly visit a focal tract that experiences the opening of a large new employer. We leverage these employer openings as an instrumental variable for exogenous increases in joint visits to A and estimate the local average treatment effect of mutual-destination mobility on subsequent B to C flows, controlling for lagged mobility. Contrary to canonical expectations of triadic closure, we find strong evidence of triadic repulsion: exogenous increases in joint visits to A reduce direct mobility between B and C, with particularly large negative effects for “bridged” dyads whose shortest geodesic paths run through A and null effects for non-bridged dyads. These results suggest that when everyday mobility flows converge on shared hubs, they consolidate activity rather than knitting alters together, challenging standard closure-based intuitions in network theory and underscoring the importance of modeling everyday mobility networks as complex, higher-order structures.