Authors: Aušra Mackutė-Varoneckienė; Ka Lok Man; Tomas Krilavičius
Addresses: Informatics Faculty, Vytautas Magnus University, Kaunas, Lithuania ' Department of Computer Science & Software Engineering, China Xi'an Jiaotong-Liverpool University, Suzhou, China ' Baltic Institute of Advanced Technology, Vilnius, Lithuania; Informatics Faculty, Vytautas Magnus University, Kaunas, Lithuania
Abstract: Quantitative methods are becoming more and more important in political science. However, they are not applicable without computers and computer based systems. In this paper we apply natural language technologies, mainly text classification, to categorise bills of the Lithuanian parliament into the predefined groups for further use in voting analysis and in other text analytic tasks. As only the titles of bills were used, in general it can be claimed that the problem of short text classification, which is poorly explored in consideration with the Lithuanian language, is addressed in this study.
Keywords: natural language processing; Lithuanian parliament bills classification; short text classification; information technology in politics; support vector machine; Naive Bayes classification; multinomial logistic regression; classification performance.
International Journal of Information Technology and Management, 2018 Vol.17 No.1/2, pp.129 - 139
Accepted: 06 Aug 2017
Published online: 18 Jan 2018 *