Complexity of the online distrust ecosystem and its evolution

Abstract

Introduction: Collective human distrust—and its associated mis/disinformation—is one of the most complex phenomena of our time, given that approximately 70% of the global population is now online. Current examples include distrust of medical expertise, climate change science, democratic election outcomes—and even distrust of fact-checked events in the current Israel-Hamas and Ukraine-Russia conflicts.Methods: Here we adopt the perspective of the system being a complex dynamical network, in order to address these questions. We analyze a Facebook network of interconnected in-built communities (Facebook Page communities) totaling roughly 100 million users who, prior to the pandemic, were just focused on distrust of vaccines.Results: Mapping out this dynamical network from 2019 to 2023, we show that it has quickly self-healed in the wake of Facebook’s mitigation campaigns which include shutdowns. This confirms and extends our earlier finding that Facebook’s ramp-ups during COVID-19 were ineffective (e.g., November 2020). We also show that the post-pandemic network has expanded its topics and has developed a dynamic interplay between global and local discourses across local and global geographic scales.Discussion: Hence current interventions that target specific topics and geographical scales will be ineffective. Instead, our findings show that future interventions need to resonate across multiple topics and across multiple geographical scales. Unlike many recent studies, our findings do not rely on third-party black-box tools whose accuracy for rigorous scientific research is unproven, hence raising doubts about such studies’ conclusions–nor is our network built using fleeting hyperlink mentions which have questionable relevance.