Seeding a Simple Contagion

35 Pages Posted: 16 Feb 2022 Last revised: 9 Nov 2023

See all articles by Evan Sadler

Evan Sadler

Columbia University, Graduate School of Arts and Sciences, Department of Economics

Date Written: February 2, 2023

Abstract

I propose a methodology for selecting seeds to maximize contagion. First, fit a random graph model based on a coarse categorization of individuals. Then, compute a seed multiplier for each category---this describes the average number of new infections each seed generates. Finally, seed the category with the highest multiplier. Relative to existing methods, my approach consumes far less computing power---the problem scales with the number of categories, not the number of individuals---and far less data. I validate the methodology through simulations using real network data.

Keywords: Seeding, Networks

JEL Classification: D85

Suggested Citation

Sadler, Evan, Seeding a Simple Contagion (February 2, 2023). Available at SSRN: https://ssrn.com/abstract=4032812 or http://dx.doi.org/10.2139/ssrn.4032812

Evan Sadler (Contact Author)

Columbia University, Graduate School of Arts and Sciences, Department of Economics ( email )

420 W. 118th Street
New York, NY 10027
United States

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