Gentrification Without Exclusion? A SOM Neural Network Investigation on the Isola District in Milan

Abstract

The research aims to investigate the peculiarities of Gentrification in Milan by setting up a map of the phenomenon in the different urban districts. Three main dimensions have been considered: the central location, the social turnover and the buildings restoration. This analysis has allowed to identify an area which is undergoing a more intense gentrification process: the Isola district. Here a survey has been conducted by means of telephone interviews with households recently arrived in the area. On the base of the gathered information with questionnaires it was possible to identify the different profiles of the gentrifiers. The analysis has concerned the identification of:

• The driving forces of the Gentrification start-up, namely the housing demand of emerging socioeconomic categories (demand explanation), or supply of restored buildings, in previously decayed and poor central neighborhood (supply explanation);

• The “gentrifiers” profile, their family needs, they professional and educational level, their preceding dwelling, and their evaluations about the positive and negative assets of the neighborhood and the dwelling;

• The urban spatial features relevant for the process.

The Application of SOM (Self Organizing Maps) Neural Networks (NN) has clustered the interviews records identifying similarities, prototypical profiles and choice criteria.