Research on sentiment analysis of hotel reviews based on Word2vec method

Jiahua Wan; Lisha Yao; Qiang Tang

doi:10.1117/12.2646968

7 September 2022 Research on sentiment analysis of hotel reviews based on Word2vec method

Jiahua Wan, Lisha Yao, Qiang Tang

Proceedings Volume 12329, Third International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2022); 1232915 (2022) https://doi.org/10.1117/12.2646968
Event: Third International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2022), 2022, Changsha, China

Abstract

This paper takes sentiment analysis as the research direction and collects the data of users' comments on hotel rooms. The research methods used include text corpus preprocessing, Word2vec model, support vector machine, AUC value calculation, feature classification based on supervised learning method, emotion analysis and ordered logistic regression model, etc. Word2vec is used to map words into k-dimensional vector space, and PCA algorithm is used to reduce the dimensionality of the results. According to Word2vec, the comment corpus can be divided into 7 categories of feature dimensions, and then feature recognition is carried out, and emotion scores are calculated by emotion analysis technology. Finally, classify and summarize the emotional scores of each comment in different feature categories. In this paper, through the establishment of Word2vec model, the analysis of consumers' emotional tendency to the hotel, to provide the direction of improving the service level for the hotel, is conducive to the management and development of the hotel.

Citation Download Citation

Jiahua Wan, Lisha Yao, and Qiang Tang "Research on sentiment analysis of hotel reviews based on Word2vec method", Proc. SPIE 12329, Third International Conference on Artificial Intelligence and Electromechanical Automation (AIEA 2022), 1232915 (7 September 2022); https://doi.org/10.1117/12.2646968

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