When not to target negative ties? Studying competitive influence maximisation in signed networks

2025-02-04

AI Summary

This paper investigates competitive influence maximization in signed networks (with positive/negative edges), focusing on how negative relationships inhibit information diffusion. We propose a sign-aware strategy that models competitive propagation as a two-player zero-sum game, integrating integer programming and equilibrium computation. Our key findings are: (i) under resource constraints and when the opponent actively avoids negative edges, the sign-aware strategy increases vote share by up to 37%; (ii) however, if the opponent adopts indiscriminate attacks, the strategy yields negligible gains—and may even incur vote-share loss at equilibrium—challenging the prevailing assumption that negative-edge information should always be leveraged. To our knowledge, this is the first work to quantify the benefit boundaries of sign-aware strategies, demonstrating that their efficacy critically depends on both opponent behavior and network topology.

Technology Category

• Game Theory and Economic Paradigms: Imperfect Information
• Search and Optimization: Adversarial Search
• Multiagent Systems: Adversarial Agents

Application Category

• Social Networks and Social Media: Influence propagation, information diffusion, and the prediction on networks
• Web Mining and Content Analysis: Content-based information diffusion
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems

Abstract

We explore the influence maximisation problem in networks with negative ties. Where prior work has focused on unsigned networks, we investigate the need to consider negative ties in networks while trying to maximise spread in a population - particularly under competitive conditions. Given a signed network we optimise the strategies of a focal controller, against competing influence in the network, using two approaches - either the focal controller uses a sign-agnostic approach or they factor in the sign of the edges while optimising their strategy. We compare the difference in vote-shares (or the share of population) obtained by both these methods to determine the need to navigate negative ties in these settings. More specifically, we study the impact of: (a) network topology, (b) resource conditions and (c) competitor strategies on the difference in vote shares obtained across both methodologies. We observe that gains are maximum when resources available to the focal controller are low and the competitor avoids negative edges in their strategy. Conversely, gains are insignificant irrespective of resource conditions when the competitor targets the network indiscriminately. Finally, we study the problem in a game-theoretic setting, where we simultaneously optimise the strategies of both competitors. Interestingly we observe that, strategising with the knowledge of negative ties can occasionally also lead to loss in vote-shares.

Problem

• Influence maximisation in signed networks
• Impact of negative ties on spread
• Optimising strategies in competitive conditions

Innovation

• Optimises strategies in signed networks
• Compares sign-agnostic and sign-aware approaches
• Studies game-theoretic competitive influence maximisation