@InProceedings{singhal-bhattacharyya:2016:COLING,
  author    = {Singhal, Prerana  and  Bhattacharyya, Pushpak},
  title     = {Borrow a Little from your Rich Cousin: Using Embeddings and Polarities of English Words for Multilingual Sentiment Classification},
  booktitle = {Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {3053--3062},
  abstract  = {In this paper, we provide a solution to multilingual sentiment classification
	using deep learning. Given input text in a language, we  use word translation
	into English and then the embeddings of these English words to train a
	classifier. This projection into the English space plus word embeddings gives a
	simple and uniform framework for multilingual sentiment analysis. A novel idea
	is augmentation of the training data with polar words, appearing in these
	sentences, along with their polarities. This approach leads to a performance
	gain of 7-10% over traditional classifiers on many languages, irrespective of
	text genre, despite the scarcity of resources in most languages.},
  url       = {http://aclweb.org/anthology/C16-1287}
}