Abstract
In recent times a complete lack of attention to migration phenomena, in national and global policies, led to a huge concentration of foreigners in major cities of Europe and USA. This trend has been faced without effective policies and programs. Consequently, a great opportunity has been transformed in a great threat and the word immigration is generally associated with the term social security. In less than one century, Italy has been transformed from a country originating great migration flows to a country which is the destination of migration flows. The aim of this paper is to examine foreign immigration in Italy distinguishing according to nationality of foreigners. In order to analyze this phenomenon Shannon and Simpson Diversity Indices to measure the level of entropy in a distribution and the variation in categorical data have been used. The spatial dimension of migration flows has been analyzed in this paper using Spatial Autocorrelation techniques and more particularly Local Indicators of Spatial Association in order to analyze the highest values of a foreigner group considering the relationship with the surrounding municipalities.
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Murgante, B., Borruso, G. (2012). Analyzing Migration Phenomena with Spatial Autocorrelation Techniques. In: Murgante, B., et al. Computational Science and Its Applications – ICCSA 2012. ICCSA 2012. Lecture Notes in Computer Science, vol 7334. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-31075-1_50
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DOI: https://doi.org/10.1007/978-3-642-31075-1_50
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