Sentiment Classification of Documents in Serbian: The Effects of Morphological Normalization

Abstract

Sentiment classification of texts written in Serbian is still an under-researched topic. One of the open issues is how the different forms of morphological normalization affect the performances of different sentiment classifiers and which normalization procedure is optimal for this task. In this paper we assess and compare the impact of lemmatizers and stemmers for Serbian on classifiers trained and evaluated on the Serbian Movie Review Dataset.