Abstract
Establishing domain-specific sentiment lexicon based on film comments is difficult. To solve this problem, this paper proposes a method based on point mutual information to construct a film sentiment lexicon, and constructs a film evaluation sentiment lexicon to improve the accuracy of the film evaluation sentiment analysis. Firstly, K-means++ clustering is used to select positive and negative seed word sets with obvious sentimental tendency; Then, using the point mutual information (PMI) algorithm to calculate the semantic similarity between the field words and the seed words; Finally get the sentimental vocabulary in the field of film evaluation. The experimental results show that the film evaluation sentiment lexicon constructed in this paper can significantly improve the accuracy of Chinese film evaluation sentiment analysis.
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Acknowledgements
This Research work was supported in part by 2018 Cultivation Project of Top Talent in Anhui Colleges and Universities (Grant No. gxbjZD15), in part by 2019 Anhui Provincial Natural Science Foundation Project (Grant No. 1908085MF189).
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Wang, Q., Zhu, G., Zhang, S. (2020). Building Sentimental Word Lexicon for Chinese Movie Comments. In: Abawajy, J., Choo, KK., Islam, R., Xu, Z., Atiquzzaman, M. (eds) International Conference on Applications and Techniques in Cyber Intelligence ATCI 2019. ATCI 2019. Advances in Intelligent Systems and Computing, vol 1017. Springer, Cham. https://doi.org/10.1007/978-3-030-25128-4_173
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DOI: https://doi.org/10.1007/978-3-030-25128-4_173
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