Leveraging Large Amounts of Weakly Supervised Data for Multi-Language Sentiment Classification

@article{Deriu2017LeveragingLA,
  title={Leveraging Large Amounts of Weakly Supervised Data for Multi-Language Sentiment Classification},
  author={Jan Deriu and A. Lucchi and V. D. Luca and A. Severyn and S. M{\"u}ller and Mark Cieliebak and Thomas Hofmann and Martin Jaggi},
  journal={Proceedings of the 26th International Conference on World Wide Web},
  year={2017}
}
  • Jan Deriu, A. Lucchi, +5 authors Martin Jaggi
  • Published 2017
  • Computer Science
  • Proceedings of the 26th International Conference on World Wide Web
  • This paper presents a novel approach for multi-lingual sentiment classification in short texts. This is a challenging task as the amount of training data in languages other than English is very limited. Previously proposed multi-lingual approaches typically require to establish a correspondence to English for which powerful classifiers are already available. In contrast, our method does not require such supervision. We leverage large amounts of weakly-supervised data in various languages to… CONTINUE READING
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    References

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