Analysis of Tourist Hotel Impression Based on SnowNLP Model

Yijun Lin; Liying Chen; Chunfu Zhang

doi:10.2991/978-94-6463-058-9_62

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Analysis of Tourist Hotel Impression Based on SnowNLP Model

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Authors

Yijun Lin¹, Liying Chen¹, Chunfu Zhang¹^{, *}

¹School of Disciplinary Basics and Applied Statistics, Zhuhai College of Science and Technology, Zhuhai, China

^*Corresponding author. Email: 1554713378@qq.com

Corresponding Author

Chunfu Zhang

Available Online 27 December 2022.

DOI: 10.2991/978-94-6463-058-9_62 How to use a DOI?
Keywords: Jieba participle; Word2vec; SnowNLP model; LDA topic model
Abstract: This article selects the tourist comment data of BdRace's official website as a sample, the original data contains lots of noise, so the data is preprocessed and the frequency of comment keywords is statistically summarized, taking the number of occurrences of characters as the popularity to get the impression word cloud table. Secondly, combined with semantic analysis, word2vec model is used to extract five topics: service, location, facilities, health and cost performance. With the help of sentiment analysis, the SnowNLP model is used to construct a comprehensive evaluation index system to score sentiment probability, the emotional probability is weighted, summed and averaged to obtain the rating table of hotels. The results show that the evaluation scoring model established in this paper performs well on the test set, the mean square error of the total scores of hotels is 0.0288. Finally, calculating the comprehensive scores of hotels, and divide hotels with high and low comprehensive evaluation levels according to the comprehensive scores. Combined with LDA theme model, carry on the characteristic analysis to the high evaluation grade hotel, by exploring the characteristics and highlights of hotels, it provides reference for the development of tourism enterprises.
Copyright: © 2023 The Author(s)
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

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Volume Title: Proceedings of the 2nd International Conference on Internet, Education and Information Technology (IEIT 2022)
Series: Advances in Computer Science Research
Publication Date: 27 December 2022
ISBN: 10.2991/978-94-6463-058-9_62
ISSN: 2352-538X
DOI: 10.2991/978-94-6463-058-9_62 How to use a DOI?
Open Access: Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

ris enw bib

TY  - CONF
AU  - Yijun Lin
AU  - Liying Chen
AU  - Chunfu Zhang
PY  - 2022
DA  - 2022/12/27
TI  - Analysis of Tourist Hotel Impression Based on SnowNLP Model
BT  - Proceedings of the 2nd International Conference on Internet, Education and Information Technology (IEIT 2022)
PB  - Atlantis Press
SP  - 373
EP  - 378
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-058-9_62
DO  - 10.2991/978-94-6463-058-9_62
ID  - Lin2022
ER  -

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