A long line of work in social psychology has studied variations in people's susceptibility to persuasion -the extent to which they are willing to modify their opinions on a topic. This body of literature suggests an interesting perspective on theoretical models of opinion formation on social networks: in addition to considering interventions that directly modify people's intrinsic opinions, it is also natural to consider those that modify people's susceptibility to persuasion. Here, we adopt a popular model for social opinion dynamics, and formalize the opinion maximization and minimization problems where interventions happen at the level of susceptibility. We show that modeling interventions at the level of susceptibility leads to an interesting family of new questions in network opinion dynamics. We find that the questions are quite different depending on whether there is an overall budget constraining the number of agents we can target or not. We give a polynomial-time algorithm for finding the optimal target-set to optimize the sum of opinions when there are no budget constraints on the size of the target-set. We show that this problem is NP-hard when there is a budget, and that the objective function is neither submodular nor supermodular. Finally, we propose a heuristic for the budgeted opinion optimization problem and show its efficacy at finding target-sets that optimize the sum of opinions on real world networks, including a Twitter network with real opinion estimates. • Theory of computation → Social networks; Graph algorithms analysis; Exact and approximate computation of equilibria; KEYWORDS social networks, opinion dynamics, influence models ACM Reference Format:
Abebe et al. REF study a similar problem (opinion maximization or minimization), but where interventions happen at the level of susceptibility to persuasion.
Opinion Dynamics with Varying Susceptibility to Persuasion
Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining
Computer Science Physics