Source-linked AI summary
New Online Ecology of Adversarial Aggregates: ISIS and beyond
N. F. Johnson, M. Zheng, Y. Vorobyeva, A. Gabriel, H. Qi, N. Velasquez, P. Manrique, D. Johnson, E. Restrepo, C. Song, S. Wuchty
TL;DR
The paper examines how extremist support persists online and may be connected to real-world groups or self-radicalized actors. It analyzes longitudinal online-support records and develops a mathematical model of aggregate dynamics, finding a power-law size distribution and predicting that disruption of smaller aggregates can thwart larger ones.
Problem
Extremist entities can use the Internet’s global reach and speed for propaganda and recruiting, and online activity may connect to organized attacks or inspire self-radicalized actors.
Source: p. 2Method
The study analyzes longitudinal online-support records for ISIS and civil protestors and develops a mathematical model of aggregate dynamics.
Source: pp. 2, 4Results
The model yields a power-law aggregate-size distribution with α=2.5, close to the empirical α=2.33 distribution.
Source: p. 4Takeaways & Limitations
Breaking up smaller aggregates can thwart the development of large, potentially more potent aggregates.
Source: p. 4
Abstract
from arXiv · showhide
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.
Invisibility
Figure 4 illustrates how name changes, shifts in visibility, and reincarnation appear in aggregate timelines, and compares adaptations by their relative size and lifetime.
Invisibility
- Panel B distinguishes visible aggregates, whose content is open to any VKontakte user, from invisible aggregates, whose content is open only to current followers.Source: Figure 4 · p. 11
- Panel A shows aggregate timelines in which color switches indicate changes in aggregate name.Source: Figure 4 · p. 11
- Panel C depicts an aggregate disappearing from the Internet for an extended time before reappearing under another identity.Source: Figure 4 · p. 11
- Panel D compares average relative maximum size and lifetime for particular adaptations and combinations against aggregates using no adaptation.“All” combines name change, invisibility, and reincarnation.Source: Figure 4 · p. 11