Vytautas Mickevičius
Vytautas Magnus University / Baltic Institute of Advanced Technology, Kaunas, Lithuania
Tomas Krilavičius
Vytautas Magnus University / Baltic Institute of Advanced Technology, Kaunas, Lithuania
Vaidas Morkevičius
Kaunas University of Technology, Institute of Public Policy and Administration, Lithuania
Aušra Mackuté-Varoneckienė
Vytautas Magnus University, Kaunas, Lithuania
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Published in: Proceedings of the 20th Nordic Conference of Computational Linguistics, NODALIDA 2015, May 11-13, 2015, Vilnius, Lithuania
Linköping Electronic Conference Proceedings 109:28, p. 225-231
NEALT Proceedings Series 23:28, p. 225-231
Published: 2015-05-06
ISBN: 978-91-7519-098-3
ISSN: 1650-3686 (print), 1650-3740 (online)
Statistical analysis of parliamentary roll-call votes is an important topic in political science as it reveals ideological positions of members of parliament and factions. However, these positions depend on the issues debated and voted upon as well as on attitude towards the governing coalition. Therefore, analysis of carefully selected sets of roll-call votes provides deeper knowledge about members of parliament behavior. However, in order to classify roll-call votes according to their topic automatic text classifiers have to be employed, as these votes are counted in thousands. In this paper we present results of an ongoing research on thematic classification of roll-call votes of the Lithuanian Parliament. Also, this paper is a part of a larger project aiming to develop the infrastructure designed for monitoring and analyzing roll-call voting in the Lithuanian Parliament.
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