000201674 001__ 201674
000201674 005__ 20190317000007.0
000201674 037__ $$aCONF
000201674 245__ $$aMining Democracy
000201674 269__ $$a2014
000201674 260__ $$c2014
000201674 336__ $$aConference Papers
000201674 520__ $$aSwitzerland has a long tradition of direct democracy, which makes it an ideal laboratory for research on real-world politics. Similar to recent open government initiatives launched worldwide, the Swiss government regularly releases datasets related to state affairs and politics. In this paper, we propose an exploratory, data-driven study of the political landscape of Switzerland, in which we use opinions expressed by candidates and citizens on a web platform during the recent Swiss parliamentary elections, together with fine-grained vote results and parliament votes. Following this purely data-driven approach, we show that it is possible to uncover interesting patterns that would otherwise require both tedious manual analysis and domain knowledge. In particular, we show that traditional cultural and/or ideological idiosyncrasies can be highlighted and quantified by looking at vote results and pre-election opinions. We propose a technique for comparing the candidates' opinions expressed before the elections with their actual votes cast in the parliament after the elections. This technique spots politicians that do not vote consistently with the opinions that they expressed during the campaign. We also observe that it is possible to predict surprisingly precisely the outcome of nationwide votes, by looking at the outcome in a single, carefully selected municipality. Our work applies to any country where similar data is available; it points to some of the avenues created by user-generated data emerging from open government initiatives, which enable new data-mining approaches to political and social sciences.
000201674 6531_ $$aData Mining
000201674 6531_ $$aVoting Advice Applications
000201674 6531_ $$aVAA
000201674 6531_ $$aVote Prediction
000201674 6531_ $$aDimensionality Reduction
000201674 700__ $$0245633$$g161149$$aEtter, Vincent
000201674 700__ $$0244094$$g167320$$aHerzen, Julien
000201674 700__ $$g152655$$aGrossglauser, Matthias$$0241029
000201674 700__ $$aThiran, Patrick$$g103925$$0240373
000201674 7112_ $$dOctober 1-2, 2014$$cDublin, Ireland$$aACM Conference on Online Social Networks (COSN'14)
000201674 8564_ $$uhttps://infoscience.epfl.ch/record/201674/files/mining-democracy-cosn.pdf$$zPublisher's version$$s4774763$$yPublisher's version
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000201674 909CO $$qGLOBAL_SET$$pconf$$pIC$$ooai:infoscience.tind.io:201674
000201674 917Z8 $$x167320
000201674 917Z8 $$x167320
000201674 937__ $$aEPFL-CONF-201674
000201674 973__ $$rREVIEWED$$sPUBLISHED$$aEPFL
000201674 980__ $$aCONF