What Predicts Support for Political Violence? Results from a Machine Learning Meta-Reanalysis

There is significant research on support for political violence (SPV), its correlates, and interventions to reduce it. However, there is no framework for understanding who supports political violence. This article leverages the exploratory power of (causal) machine learning to conduct a registered meta-reanalysis of both the observational and experimental literature on SPV from 1995-2025 to synthesize and summarize previous research. First, we identify three categories of individual-level predictors: politically salient identities, psychological characteristics, and attitudes toward one's political system. Second, we find that young adults are the most likely to support political violence across many recent surveys, particularly in the U.S. Additionally, in two experiments in the U.S. and India we find that young people are by far the most affected by treatments aimed at both decreasing and increasing support, respectively. Third, and in contrast to research on the perpetration of violence, we find scant evidence of a relationship between gender identity and SPV.