New Online Ecology of Adversarial Aggregates: ISIS and beyond

TL;DR

This paper uncovers the dynamic online ecology of extremist groups, revealing how self-organized aggregates support extremism and proposing a mathematical model to understand and potentially disrupt these online support networks.

Contribution

It introduces a mathematical theory describing the evolving ecology of online extremist aggregates and suggests strategies to disrupt large groups by targeting smaller ones.

Findings

Self-organized online groups support extremism and proliferate before real-world campaigns.

The ecology evolves on a daily timescale with adaptive mechanisms.

Targeting smaller aggregates can prevent the growth of larger, more potent groups.

Abstract

Support for extremist entities - whether from the far right, or far left - often manages to survive globally online despite significant external pressure, and may ultimately inspire violent acts by individuals having no obvious prior history of extremism. Examining longitudinal records of extremist online activity, we uncovered an ecology evolving on a daily timescale that drives online support, and we provide a mathematical theory that describes it. The ecology features self-organized aggregates (online groups such as on Facebook or another social media analog) that proliferate preceding the onset of recent real-world campaigns, and adopt novel adaptive mechanisms to enhance their survival. One of the predictions is that development of large, potentially potent online groups can be thwarted by targeting smaller ones.