@InProceedings{phani-lahiri-biswas:2016:WSSANLP2016,
  author    = {Phani, Shanta  and  Lahiri, Shibamouli  and  Biswas, Arindam},
  title     = {Sentiment Analysis of Tweets in Three Indian Languages},
  booktitle = {Proceedings of the 6th Workshop on South and Southeast Asian Natural Language Processing (WSSANLP2016)},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {93--102},
  abstract  = {In this paper, we describe the results of sentiment analysis on tweets in three
	Indian languages -- Bengali, Hindi, and Tamil. We used the recently released
	SAIL dataset (Patra et al., 2015), and obtained state-of-the-art results in all
	three languages. Our features are simple, robust, scalable, and
	language-independent. Further, we show that these simple features provide
	better results than more complex and language-specific features, in two
	separate classification tasks. Detailed feature analysis and error analysis
	have been reported, along with learning curves for Hindi and Bengali.},
  url       = {http://aclweb.org/anthology/W16-3710}
}