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Saeed Seddighin

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Preprint Sep 2026

Maximizing Social Influence in Almost Linear Time

Influence maximization is a central algorithmic challenge in network analysis, aiming to identify a set of $k$ seed nodes in a graph with $n$ nodes and $m$ edges that maximizes the expected cascade of information under standard diffusion models. The seminal work of Borgs, Brautbar, Chayes, and Lucier (SODA'14) yielded...

Saeed Seddighin · 1 citation