@InProceedings{deriu-EtAl:2017:SocialNLP2017,
  author    = {Deriu, Jan Milan  and  Weilenmann, Martin  and  Von Gruenigen, Dirk  and  Cieliebak, Mark},
  title     = {Potential and Limitations of Cross-Domain Sentiment Classification},
  booktitle = {Proceedings of the Fifth International Workshop on Natural Language Processing for Social Media},
  month     = {April},
  year      = {2017},
  address   = {Valencia, Spain},
  publisher = {Association for Computational Linguistics},
  pages     = {17--24},
  abstract  = {In this paper we investigate the cross-domain performance of a current
	state-of-the-art sentiment analysis systems. For this purpose we train a
	convolutional neural network (CNN) on data from different domains and evaluate
	its performance on other domains. Furthermore, we evaluate the usefulness of
	combining a large amount of different smaller annotated corpora to a large
	corpus. Our results show that more sophisticated approaches are required to
	train a system that works equally well on various domains.},
  url       = {http://www.aclweb.org/anthology/W17-1103}
}