@InProceedings{rotim-vsnajder:2017:BSNLP,
  author    = {Rotim, Leon  and  \v{S}najder, Jan},
  title     = {Comparison of Short-Text Sentiment Analysis Methods for Croatian},
  booktitle = {Proceedings of the 6th Workshop on Balto-Slavic Natural Language Processing},
  month     = {April},
  year      = {2017},
  address   = {Valencia, Spain},
  publisher = {Association for Computational Linguistics},
  pages     = {69--75},
  abstract  = {We focus on the task of supervised sentiment classification of short and
	informal texts in Croatian, using two simple yet effective methods: word
	embeddings and string kernels. We investigate whether word embeddings offer any
	advantage over corpus- and preprocessing-free string kernels, and how these
	compare to bag-of-words baselines. We conduct a comparison on three different
	datasets, using different preprocessing methods and kernel functions. Results
	show that, on two out of three datasets, word embeddings outperform string
	kernels, which in turn outperform word and n-gram bag-of-words baselines.},
  url       = {http://www.aclweb.org/anthology/W17-1411}
}