@InProceedings{sun-EtAl:2018:WASSA2018,
  author    = {Sun, Baohua  and  Yang, Lin  and  Dong, Patrick  and  Zhang, Wenhan  and  Dong, Jason  and  Young, Charles},
  title     = {Super Characters: A Conversion from Sentiment Classification to Image Classification},
  booktitle = {Proceedings of the 9th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis},
  month     = {October},
  year      = {2018},
  address   = {Brussels, Belgium},
  publisher = {Association for Computational Linguistics},
  pages     = {309--315},
  abstract  = {We propose a method named Super Characters for sentiment classification. This method converts the sentiment classification problem into image classification problem by projecting texts into images and then applying CNN models for classification. Text features are extracted automatically from the generated Super Characters images, hence there is no need of any explicit step of embedding the words or characters into numerical vector representations. Experimental results on large social media corpus show that the Super Characters method consistently outperforms other methods for sentiment classification and topic classification tasks on ten large social media datasets of millions of contents in four different languages, including Chinese, Japanese,Korean and English.},
  url       = {http://aclweb.org/anthology/W18-6245}
}