Minimal contagious sets: Degree distributional bounds

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.

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Publication Details

Journal
Journal of Economic Theory
Published
2025-04-14
DOI
https://doi.org/10.1016/j.jet.2025.106009
Citations
1
Primary Topic
Opinion Dynamics and Social Influence
Type
article
Field-Weighted Citation Impact
0.00

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article

Minimal contagious sets: Degree distributional bounds

Ron Peretz, Itai Arieli, Yevgeny Tsodikovich, Galit Ashkenazi-Golan
1 citations
Journal of Economic Theory
Opinion Dynamics and Social Influence
article

Minimal contagious sets: Degree distributional bounds

Ron Peretz, Itai Arieli, Yevgeny Tsodikovich, Galit Ashkenazi-Golan
article en
1 citations

Abstract

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.

Journal of Economic TheoryVol. 226
Ben-Gurion University of the Negev (IL), Bar-Ilan University (IL), Technion – Israel Institute of Technology (IL), London School of Economics and Political Science (GB)
Israel Science Foundation
Openalex Percentile: Top 94%
Opinion Dynamics and Social Influence
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