Emoticon Smoothed Language Models for Twitter Sentiment Analysis

@article{Liu2012EmoticonSL,
  title={Emoticon Smoothed Language Models for Twitter Sentiment Analysis},
  author={Kun Liu and Wu-Jun Li and Minyi Guo},
  journal={Proceedings of the AAAI Conference on Artificial Intelligence},
  year={2012}
}
  • Kun Liu, Wu-Jun Li, M. Guo
  • Published 22 July 2012
  • Computer Science
  • Proceedings of the AAAI Conference on Artificial Intelligence
Twitter sentiment analysis (TSA) has become a hot research topic in recent years. The goal of this task is to discover the attitude or opinion of the tweets, which is typically formulated as a machine learning based text classification problem. Some methods use manually labeled data to train fully supervised models, while others use some noisy labels, such as emoticons and hashtags, for model training. In general, we can only get a limited number of training data for the fully supervised… 
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