In “Effectiveness variation in simulated school‑based network interventions” the team applied simulations to 17 real school friendship networks, comparing seven different strategies for seeding adoption. They found that selecting the most popular students (nodes with high degree) was generally effective across many diffusion scenarios.

However, their findings also demonstrate that effectiveness varied significantly depending on network structure and whether the contagion process was ‘simple’ (one contact triggers adoption) or ‘complex’ (requires multiple adopted neighbours). For complex contagion especially, some seed strategies failed to trigger any spread at all.

This highlights that it is not enough to pick “popular” individuals, intervention developers must also account for how behaviours propagate (thresholds, peer reinforcement) and the underlying network topology (community structure, path-lengths, diameter, etc).