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2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) (2016)
San Francisco, CA, USA
Aug. 18, 2016 to Aug. 21, 2016
ISBN: 978-1-5090-2847-4
pp: 1270-1277
Mauro Coletto , IMT School for Advanced Studies Lucca
Andrea Esuli , ISTI - CNR Pisa
Claudio Lucchese , ISTI - CNR Pisa
Cristina Ioana Muntean , ISTI - CNR Pisa
Franco Maria Nardini , ISTI - CNR Pisa
Raffaele Perego , ISTI - CNR Pisa
Chiara Renso , ISTI - CNR Pisa
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 a 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.
Twitter, Tagging, Europe, Data mining, Urban areas, Media
Mauro Coletto, Andrea Esuli, Claudio Lucchese, Cristina Ioana Muntean, Franco Maria Nardini, Raffaele Perego, Chiara Renso, "Sentiment-enhanced multidimensional analysis of online social networks: Perception of the mediterranean refugees crisis", 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM), vol. 00, no. , pp. 1270-1277, 2016, doi:10.1109/ASONAM.2016.7752401
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