TY - JOUR
T1 - Minimal contagious sets
T2 - Degree distributional bounds
AU - Arieli, Itai
AU - Ashkenazi-Golan, Galit
AU - Peretz, Ron
AU - Tsodikovich, Yevgeny
N1 - Publisher Copyright:
© 2025 The Author(s)
PY - 2025/5/1
Y1 - 2025/5/1
N2 - Agents in a network adopt an innovation if a certain fraction of their neighbors has already done so. We study the minimal contagious set size required for a successful innovation adoption by the entire population, and provide upper and lower bounds on it. Since detailed information about the network structure is often unavailable, we study bounds that depend only on the degree distribution of the network – a simple statistic of the network topology. Moreover, as our bounds are robust to small changes in the degree distribution, they also apply to large networks for which the degree distribution can only be approximated. Applying our bounds to growing networks shows that the minimal contagious set size is linear in the number of nodes. Consequently, for outside of knife-edge cases (such as the star-shaped network), contagion cannot be achieved without seeding a significant fraction of the population. This finding highlights the resilience of networks and demonstrates a high penetration cost in the corresponding markets.
AB - Agents in a network adopt an innovation if a certain fraction of their neighbors has already done so. We study the minimal contagious set size required for a successful innovation adoption by the entire population, and provide upper and lower bounds on it. Since detailed information about the network structure is often unavailable, we study bounds that depend only on the degree distribution of the network – a simple statistic of the network topology. Moreover, as our bounds are robust to small changes in the degree distribution, they also apply to large networks for which the degree distribution can only be approximated. Applying our bounds to growing networks shows that the minimal contagious set size is linear in the number of nodes. Consequently, for outside of knife-edge cases (such as the star-shaped network), contagion cannot be achieved without seeding a significant fraction of the population. This finding highlights the resilience of networks and demonstrates a high penetration cost in the corresponding markets.
KW - Attachment
KW - Contagious
KW - Diffusion
KW - Innovation
KW - Word-of-mouth
UR - https://www.scopus.com/pages/publications/105002490337
U2 - 10.1016/j.jet.2025.106009
DO - 10.1016/j.jet.2025.106009
M3 - Article
AN - SCOPUS:105002490337
SN - 0022-0531
VL - 226
JO - Journal of Economic Theory
JF - Journal of Economic Theory
M1 - 106009
ER -