@inproceedings{singhal-bhattacharyya-2016-borrow,
    title = "Borrow a Little from your Rich Cousin: Using Embeddings and Polarities of {E}nglish Words for Multilingual Sentiment Classification",
    author = "Singhal, Prerana  and
      Bhattacharyya, Pushpak",
    editor = "Matsumoto, Yuji  and
      Prasad, Rashmi",
    booktitle = "Proceedings of {COLING} 2016, the 26th International Conference on Computational Linguistics: Technical Papers",
    month = dec,
    year = "2016",
    address = "Osaka, Japan",
    publisher = "The COLING 2016 Organizing Committee",
    url = "https://preview.aclanthology.org/fix-sig-urls/C16-1287/",
    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."
}