Abstract
We consider the problem of budget allocation for competitive influence maximization over social networks. In this problem, multiple competing parties (players) want to distribute their limited advertising resources over a set of social individuals to maximize their long-run cumulative payoffs. It is assumed that the individuals are connected via a social network and update their opinions based on the classical DeGroot model. The players must decide on the budget distribution among the individuals at a finite number of campaign times to maximize their overall payoff as a function of individuals' opinions. Under some assumptions, we show that i) the optimal investment strategy for a single player can be found in polynomial time by solving a concave program, and ii) the open-loop equilibrium strategies for the multiplayer dynamic game can be computed efficiently by following natural regret-minimization dynamics. Our results extend earlier work on the static version of the problem to a dynamic multistage game.
Original language | English (US) |
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Pages (from-to) | 1496-1500 |
Number of pages | 5 |
Journal | IEEE Control Systems Letters |
Volume | 6 |
DOIs | |
State | Published - 2022 |
Keywords
- Opinion dynamics
- convex optimization
- dynamic games
- network resource allocation
- open-loop Nash equilibrium
- social networks
ASJC Scopus subject areas
- Control and Systems Engineering
- Control and Optimization