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摘要
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I propose a method for selecting seeds to maximize contagion. First, fit a random graph model using a coarse categorization of individuals. Next, compute a seed multiplier for each category-this is the average number of new infections a seed generates. Finally, seed the category with the highest multiplier. Relative to the most common methods, my approach requires far less granular data, and it consumes less computing power-the problem scales with the number of categories, not the number of individuals. I validate the methodology through simulations using real network data.
Keyword:
Seeding
networks
configuration model
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7.1
论文数:
3.0K
被引数:
4.3W
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Network-based marketing: Identifying likely adopters via consumer networks.png)
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