(R&R at the American Economic Review; with Mohammad Akbarpour and Amin Saberi)
Identifying the optimal set of individuals to first receive information in a social network is a widely-studied problem in settings such as the diffusion of information, microfinance programs, and new technologies. We show that, for some frequently studied diffusion processes, randomly seeding S + X individuals can prompt a larger cascade than optimally targeting the best S individuals, for a small X. Given these findings, practitioners interested in communicating a message to a large number of people may wish to compare the cost of network-based targeting to that of slightly expanding initial outreach.
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