@InProceedings{li-lu-long:2017:I17-2,
  author    = {Li, Minglei  and  Lu, Qin  and  Long, Yunfei},
  title     = {Are Manually Prepared Affective Lexicons Really Useful for Sentiment Analysis},
  booktitle = {Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 2: Short Papers)},
  month     = {November},
  year      = {2017},
  address   = {Taipei, Taiwan},
  publisher = {Asian Federation of Natural Language Processing},
  pages     = {146--150},
  abstract  = {In this paper, we investigate the effectiveness of different affective lexicons
	through sentiment analysis of phrases. We examine how phrases can be
	represented through manually prepared lexicons, extended lexicons using
	computational methods, or word embedding. Comparative studies clearly show that
	word embedding using unsupervised distributional method outperforms manually
	prepared lexicons no matter what affective models are used in the lexicons. Our
	conclusion is that although different affective lexicons are cognitively backed
	by theories, they do not show any advantage over the automatically obtained
	word embedding.},
  url       = {http://www.aclweb.org/anthology/I17-2025}
}