Control of Harmful Information Spreading on Adaptive Higher-Order Networks via Group Dissolution

Abstract

Curbing harmful information contagion remains a critical challenge, motivating platform-level interventions such as group dissolution to sever transmission chains. However, in practice, users affected by dissolution often exhibit adaptive behavior, rewiring to form new groups. Yet, it remains unclear how these two mechanisms jointly shape information contagion and whether group dissolution remains effective in suppressing it. Here, we develop an adaptive higher-order contagion model that integrates platform-induced group dissolution with user adaptive rewiring, and derive a theoretical framework. Notably, we reveal an effective window for group dissolution, bounded by a critical infection rate. Above this threshold, dissolution backfires and amplifies information prevalence. Within this window, dissolution acts non-monotonically, initially exacerbating prevalence before eradicating contagion via a discontinuous transition beyond a critical dissolution rate. We further show that higher-order reinforcement expands this infection-rate window over which dissolution remains effective, whereas rewiring homophily substantially narrows it. Simulations on empirical hypergraph also validate these findings. Our work highlights the interplay between top-down platform interventions and bottom-up user adaptation, underscoring the need to account for adaptive responses when designing strategies to curb harmful information without unintended amplification.