#immigrants project: the on-line perception of integration

Abstract

[EN] This paper analyses the content of Twitter’s comments during the period covering the last European elections. "#immigrants" is the extraction’s keyword in different national languages. With the exception of English and French, whose extraction would be misleading, all of the other languages have been chosen to catch the geographical area of reference. We made sure to extract at least two sentences for each Welfare area. Once the data have been extracted, three different strategies have been used. The first one, dealing with both a qualitative and a quantitative assessment; the second one, analysing automatically the content of the top 10 extracted tweets during the reference period and the third one based on network analysis. Through a deep analysis of the content, three clusters have been identified: the first one dealing with the cultural risks of multiculturalism; the second one (social risks) dealing with the fear of migrants stealing job vacancies and the third one dealing with economic risks. A deep network analysis of Italian and Spanish contexts follows. What emerges is that: communication is extremely heterogeneous; in Italy there unique and duplicated edges prevails; in Spain there are more groups than in Italy, more themes covered and different kind of users and nets.