Abstract
This paper aims at demonstrating sentiment strength analysis in aspect-based opinion mining. Previous works normally focused on reviewers’ sentiment orientation and ignored sentiment strength that users expressed in the reviews. In order to offset this disadvantage, two methods for sentiment strength evaluation were proposed. Experiments on a huge hotel review dataset show how sentiment strength analysis can improve the performance of aspect rating prediction.
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Acknowledgements
We would like to thank the National Natural Science Foundation of China (Grant No. 61375053) for part of the financial support of this paper.
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Wang, Y., Huang, Y., Wang, M. (2017). Aspect-Based Rating Prediction on Reviews Using Sentiment Strength Analysis. In: Benferhat, S., Tabia, K., Ali, M. (eds) Advances in Artificial Intelligence: From Theory to Practice. IEA/AIE 2017. Lecture Notes in Computer Science(), vol 10351. Springer, Cham. https://doi.org/10.1007/978-3-319-60045-1_45
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