Sentiment analysis based on clustering: a framework in improving accuracy and recognizing neutral opinions

@article{Li2013SentimentAB,
  title={Sentiment analysis based on clustering: a framework in improving accuracy and recognizing neutral opinions},
  author={Gang Li and Fei Liu},
  journal={Applied Intelligence},
  year={2013},
  volume={40},
  pages={441-452}
}
Clustering-based sentiment analysis is a novel approach for analyzing opinions expressed in reviews, comments or blogs. In contrast to the two traditional mainstream approaches (supervised learning and symbolic techniques), the clustering-based approach is able to produce basically accurate analysis results without any human participation, linguist knowledge or training time. This paper introduces new techniques designed to extend the capability of the clustering-based sentiment analysis… CONTINUE READING

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