Conspiracy to commit: Information pollution, artificial intelligence, and real-world hate crime

• In Event: Information pollution

Abstract

Is the consumption of online conspiracy theories linked to real-world hate crimes? By analyzing online search trends for 36 racially and politically charged conspiracy theories in Michigan (2015–2019), we employ a one-dimensional convolutional neural network (1D-CNN) to predict hate crime occurrences offline. A subset of theories—including Rothschilds, Q-Anon, and The Great Replacement—improves prediction accuracy, with effects emerging two to three weeks after spikes in searches. However, most theories showed no clear connection to offline hate crimes. Aligning with neutralization and differential association theories, our findings empirically link specific racially charged conspiracy theories to real-world violence. This study underscores the potential of machine learning in identifying harmful online patterns and advancing social science research.

Authors

• Alberto Aziani, Università degli Studi di Milano-Bicocca

• Michael Lo Giudice, Transcrime-Università Cattolica del Sacro Cuore

• Ali Shadman Yazdi, Politecnico di Milano