@InProceedings{ljubevsic-fivser:2016:WNUT,
  author    = {Ljube\v{s}i\'{c}, Nikola  and  Fi\v{s}er, Darja},
  title     = {Private or Corporate? Predicting User Types on Twitter},
  booktitle = {Proceedings of the 2nd Workshop on Noisy User-generated Text (WNUT)},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {4--12},
  abstract  = {In this paper we present a series of experiments on discriminating between
	private and corporate accounts on Twitter. We define features based on Twitter
	metadata, morphosyntactic tags and surface forms, showing that the simple
	bag-of-words model achieves single best results that can, however, be improved
	by building a weighted soft ensemble of classifiers based on each feature type.
	Investigating the time and language dependence of each feature type delivers
	quite unexpecting results showing that features based on metadata are neither
	time- nor language-insensitive as the way the two user groups use the social
	network varies heavily through time and space.},
  url       = {http://aclweb.org/anthology/W16-3904}
}