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.
| Original language | English |
|---|---|
| Pages (from-to) | 129-139 |
| Number of pages | 11 |
| Journal | International Journal of Information Technology and Management |
| Volume | 17 |
| Issue number | 1-2 |
| DOIs | |
| Publication status | Published - 2018 |
Keywords
- Classification performance
- Information technology in politics
- Lithuanian parliament bills classification
- Multinomial logistic regression
- Naive Bayes classification
- Natural language processing
- Short text classification
- Support vector machine