City riots fed by transnational and trans-topic web-of-influence

TL;DR

This study uncovers a transnational web of online hate and extremism that predates and influences large-scale city riots, highlighting the importance of multi-platform monitoring for early threat detection.

Contribution

It reveals a persistent, multi-scale online influence network feeding into riots, emphasizing the need for coordinated international monitoring and intervention strategies.

Findings

Online hate communities existed before riots

Video platforms were primary channels of influence

The influence web shows resilience and international reach

Abstract

The sudden emergence of large-scale riots in otherwise unconnected cities across the UK in summer 2024 came as a shock for both government officials and citizens. Irrespective of these riots' specific trigger, a key question is how the capacity for such widespread city rioting might be foreseen through some precursor behavior that flags an emerging appetite for such rioting at scale. Here we show evidence that points toward particular online behavior which developed at scale well ahead of the riots, across the multi-platform landscape of hate/extremist communities. Our analysis of detailed multi-platform data reveals a web-of-influence that existed well before the riots, involving online hate and extremism communities locally, nationally, and globally. This web-of-influence fed would-be rioters in each city mainly through video platforms. This web-of-influence has a persistent resilience -- and hence still represents a significant local, national, and international threat in the future -- because of its feedback across regional-national-international scales and across topics such as immigration; and its use of multiple lesser-known platforms that put it beyond any single government or platform's reach. Going forward, our findings mean that if city administrators coordinate with each other across local-national-international divides, they can map this threat as we have done here and initiate deliberation programs that might then soften such pre-existing extremes at scale, perhaps using automated AI-based technology.