Digital Darkness: Quantifying the Relationship Between Internet Shutdowns and Digital Authoritarian Control

This study employs novel quantitative methods to analyze the relationship between internet shutdowns and the consolidation of digital authoritarian control across 42 countries from 2018-2024. Using machine learning analysis of shutdown data, social unrest indicators, and regime characteristics, we demonstrate that internet shutdowns serve as both tactical tools and strategic signals in digital authoritarian governance. Our findings reveal that countries experiencing frequent shutdowns show a 68% higher likelihood of implementing permanent digital control infrastructure within 24 months. Through Python-based analysis combining shutdown duration data, protest events, and subsequent surveillance system deployments, we identify distinct patterns where temporary shutdowns precede permanent control mechanisms. Notably, regimes that initially rely on shutdowns transition to more sophisticated content filtering and surveillance systems 83% of the time, suggesting shutdowns often serve as temporary measures while building permanent digital control infrastructure. This research provides empirical evidence of shutdowns as leading indicators of expanding digital authoritarianism, contributing to both theoretical understanding and early warning capabilities for democracy advocates.