Analysing voting behavior of the Lithuanian parliament using cluster analysis and multidimensional scaling : technical aspects

Rational models of electoral behavior emphasize the need of sufficient information for voters to make their decisions. Monitoring the behavior of a single politician is not easy to implement, not to mention of the whole parliament, since for the latter one must apply statistical methods designed for the analysis of large amounts of information. In this paper we propose methods and techniques for the analysis of voting behavior of the Lithuanian Parliament (Seimas) that allow for clearer identification and recognition of voting patterns of the Seimas. Votes of the last sessions of the 2008-2012 term of the Seimas (pre-election period) are analyzed employing cluster analysis. Also, multidimensional scaling is used to visualize the generated results. Results obtained using different vote coding methods and clustering techniques are compared in the paper, too.