National internal security policies across Europe – a comparative analysis applying big data clustering techniques

Abstract

ABSTRACT Our contribution examines two questions regarding the internal security policies of 28 European countries: First, the question which different internal security conceptions regarding crime management exist and second, how countries cluster along these conceptions. As data foundation, we use a two-dimensional approach examining the dimensions of capabilities and punitivity with two variables for each. For the dimension of capabilities, we utilize the spending share of government budget for internal security and the relative number of police officers and for the punitivity dimension, we consider average prison terms and the share of alternatives to conventional incarceration. By using this data in combination with modern clustering techniques, we prove that our results are stable and cohesive despite the wide variety of different methods and clustering techniques deployed, which include state-of-the-art unsupervised learning algorithms adapted from big data frameworks. By also including most Eastern European Countries in a comparative European setup for the first time, we identify five different clusters, namely a Western and Central European Cluster, a liberal Scandinavian cluster, two different Southern and Eastern European clusters with high capabilities and very uneven levels of punitivity, and one cluster with special cases with very infrequent use of alternatives to conventional punishment.