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Влияние информационно-коммуникационных технологий на политическую стабильность в меняющемся мире: кросс-страновой количественный анализ
The development and spread of the Internet in recent decades have become one of the most important global processes covering all regions of the world. Like all processes of this scale, it creates a complex system of opportunities and risks at all levels. In this work, the authors focus on such a dimension as the risks to the internal stability of states generated by mass protest movements. States with different political regimes associate the spread of the Internet with a threat to the stability of the internal political order, as evidenced by the global trend of increasing efforts to organize politically motivated censorship of the Internet content. Which of these processes – growing coordination and information capabilities of protest movements or increasing state influence on the global network – has a greater impact on protest activity? And what direction does this impact have? In order to answer these questions, the authors undertook a quantitative study of a panel data on 160 countries in 1990–2019. The key independent variables were the levels of Internet penetration (World Bank data) and state Internet censorship (V-Dem), the dependent variable was the maximum number of protesters per year (Mass Mobilization Project). The results of ordinal logistic regression demonstrate that there was not the Internet penetration per se, but the state’s response to the development of Internet technologies plays the most important role in the relationship between information and communication technologies and the scale of street protest activity. This relationship is nonlinear, it has a quadratic n-shape. The maximum number of protesters is achieved, although at a high, but still not at the maximum level of Internet freedom from censorship. At the same time, total censorship is indeed robustly associated with the absence of street protest mobilization. The identified pattern can be traced both within the full dataset and within each of the three main chronological eras of the development of the Internet: 1995–2005, 2006–2015, and 2016–2019.