  Previous studies have offered a variety of explanations on the relationship
between democracy and the internet. 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. Drawing upon the
International Telecommunication Union, Freedom House, and World Bank databases
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. The comparison of the various machine
learning models reveals that the best predicting model is the 175-tree random
forest model which has 92% accuracy. Also, this study might help "IT
professionals" to see their important role not only in the technical fields but
also in society in terms of democratization and how close IT is to social
sciences.
