  We propose an analytical framework able to investigate discussions about
polarized topics in online social networks from many different angles. The
framework supports the analysis of social networks along several dimensions:
time, space and sentiment. We show that the proposed analytical framework and
the methodology can be used to mine knowledge about the perception of complex
social phenomena. We selected the refugee crisis discussions over Twitter as
the case study. This difficult and controversial topic is an increasingly
important issue for the EU. The raw stream of tweets is enriched with space
information (user and mentioned locations), and sentiment (positive vs.
negative) w.r.t. refugees. Our study shows differences in positive and negative
sentiment in EU countries, in particular in UK, and by matching events,
locations and perception it underlines opinion dynamics and common prejudices
regarding the refugees.
