text_combined: aleks jakulin boowjniacmorg apologies seen arent interested us politics taken us senate roll call voting data disclose senators voted particular issue lot 100 senators almost 500 issues per year several organizations examine friendly individual senators ordinary voter much hassle political scientists however regularly observe datasets specialpurpose models objective check usual algorithms normally use field work turns data mining tools quite complementary already used political science lots things clustering senators hierarchically discrete mixture modelling identify social networks based similarly senators vote evaluate influential senator whole state particular group senators use informationtheoretic ideas represent senators 2d ideology space use vrml 3d visualizations perform whatif analysis could overturned particular bill disagreement inside party youre interested check httpwwwailabsialekspolitics used generalpurpose orange data mining toolkit httpwwwailabsiorange python gpl furthermore used mpca discrete probabilistic principal components modeling kit httpcoscohiitfisearchmpca also gpl identify blocs senate scripts data freely available also two working papers discuss everything detail mag aleks jakulin httpwwwailabsialeks artificial intelligence laboratory faculty computer information science university ljubljana slovenia tue 05 aug 2008 184532 0700 uai data mining political data