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Filtrado por: Creador Sagir, Mustafa Eliminar la restricciónCreador: Sagir, Mustafa Departamento - School of Information Technology Eliminar la restricciónDepartamento: - School of Information Technology

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  • Explaining the Relationship between Internet and Democracy in Partly Free Countries Using Machine Learning Models

    Article thumbnail: Explaining the Relationship between Internet and Democracy in Partly Free Countries Using Machine Learning Models
    Type:
    Article
    Descripción/Resumen:
    Previous studies have offered a variety of explanations on the relationship between democracy and the internet. Some argue that with free access to information, knowledge sharing without any constraint, and the spread of political knowledge, the internet will help change people’s political attitudes and spread democracy. Other studies found that authoritarian regimes by censoring the internet, tracking the political activist, prosecuting the dissidents, and using the internet to spread their propaganda limit the democratization. Also, some studies explored the effects of diffusion of false news through the internet and especially via social media. However, most of these studies concentrate on regions, specific states or authoritarian regimes. No study has investigated the influence of the internet in partly free countries defined by the Freedom House. Moreover, very little is known about the effects of online censorship on the development, stagnation, or decline of democracy. To fully understand the impact of the internet and online censorship on democratization in partly free countries, we must explore these relationships in these countries. Drawing upon the International Telecommunication Union, Freedom House, and World Bank reports and using machine learning methods, this study sheds new light on the effects of the internet on democratization in partly free countries. The findings suggest that internet penetration and online censorship both have a negative impact on democracy scores and the internet’s effect on democracy scores is conditioned by online censorship. Moreover, results from random forest suggest that online censorship is the most important variable followed by governance index and education on democracy scores.
    Creador/Autor:
    Varlioglu, M. Said and Sagir, Mustafa
    Peticionario:
    Jess Kropczynski
    Fecha modificada:
    05/15/2020
    Fecha modificada:
    05/15/2020
    Fecha de creacion:
    2020-04-14
    Licencia:
    All rights reserved