Advances in Economics, Management and Political Sciences

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Proceedings of the 7th International Conference on Economic Management and Green Development

Series Vol. 44 , 10 November 2023


Open Access | Article

User Sentiment Analysis Based on Online Reviews -Taking the Forbidden City Afternoon Tea Restaurant as an Example

Sijia Zheng * 1
1 Beijing Jiaotong University

* Author to whom correspondence should be addressed.

Advances in Economics, Management and Political Sciences, Vol. 44, 116-122
Published 10 November 2023. © 2023 The Author(s). Published by EWA Publishing
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Citation Sijia Zheng. User Sentiment Analysis Based on Online Reviews -Taking the Forbidden City Afternoon Tea Restaurant as an Example. AEMPS (2023) Vol. 44: 116-122. DOI: 10.54254/2754-1169/44/20232202.

Abstract

Nowadays, Internet consumption has become a familiar name, and there are more and more feedback channels on the production experience of consumers, and the content of evaluation also determines consumers' views on the goods to a certain extent. Therefore, the rational use of online comment contents can not only help consumers understand the basic information of products, but also help enterprises to better obtain the needs of consumers and provide more references for them. This paper selects the comment data of the Palace restaurant in Dianping software, and uses Python software to conduct data mining, emotion analysis, word frequency statistics and word cloud drawing. The conclusion shows that consumers have a positive emotional tendency towards the afternoon tea in the Palace Museum, with few negative comments. At the same time, consumers pay more attention to the dining location and food ingredients. Therefore, businesses can increase the improvement of dishes and environmental transformation through online reviews to better meet the needs of consumers. This research not only provides the basis for the evaluation of the business level, but also helps to enrich the consumer's understanding of the business.

Keywords

Python, online review, text mining, emotion analysis

References

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Data Availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

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Volume Title
Proceedings of the 7th International Conference on Economic Management and Green Development
ISBN (Print)
978-1-83558-109-4
ISBN (Online)
978-1-83558-110-0
Published Date
10 November 2023
Series
Advances in Economics, Management and Political Sciences
ISSN (Print)
2754-1169
ISSN (Online)
2754-1177
DOI
10.54254/2754-1169/44/20232202
Copyright
10 November 2023
Open Access
This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited

Copyright © 2023 EWA Publishing. Unless Otherwise Stated