Research Article
Evaluating Attitude Shift From Tourism Online Reviews Using Word Embedding-Based Approaches
@INPROCEEDINGS{10.4108/eai.18-11-2022.2327170, author={Binyan Chen and Yishi Zhang and Wenjie Chen}, title={Evaluating Attitude Shift From Tourism Online Reviews Using Word Embedding-Based Approaches}, proceedings={Proceedings of the 4th International Conference on Economic Management and Model Engineering, ICEMME 2022, November 18-20, 2022, Nanjing, China}, publisher={EAI}, proceedings_a={ICEMME}, year={2023}, month={2}, keywords={online reviews; review usefulness; sentiment analysis; word embedding; deep learning}, doi={10.4108/eai.18-11-2022.2327170} }- Binyan Chen
Yishi Zhang
Wenjie Chen
Year: 2023
Evaluating Attitude Shift From Tourism Online Reviews Using Word Embedding-Based Approaches
ICEMME
EAI
DOI: 10.4108/eai.18-11-2022.2327170
Abstract
The shift of consumers' attitudes caused by public health emergencies can be reflected in online reviews. This study applies the word embedding-based methods and sentiment propensity analysis to mine tourism online reviews. Specifically, we obtain the comprehensive vector of each review, which consists of the word vectors in the review word embedding, and evaluate the changes in tourists' emotional tendencies in the context of public health emergencies (taking COVID-19 as an example). The empirical results verify the effectiveness of the word embedding-based methods in identifying attitude shift and confirm the divergent effect of emotional valence in predicting the usefulness of tourism online reviews.
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