Sentiment Analysis for Hotel Reviews: A Systematic Literature Review

Author:

Ameur Asma1ORCID,Hamdi Sana2ORCID,Ben Yahia Sadok3ORCID

Affiliation:

1. Polytechnic School of Tunisia & LIPAH, LR111417, Tunis El Manar University, Faculty of Sciences of Tunis, Tunisia

2. LIPAH, LR111417, Tunis El Manar University, Faculty of Sciences of Tunis, Tunisia

3. Department of Software Science, Tallinn University of Technology, Estonia

Abstract

Sentiment Analysis (SA) helps to automatically and meaningfully discover hotel customers’ satisfaction from their shared experiences and feelings on social media. Several studies have been conducted to improve the precision of SA in the hospitality industry, which vary in data preprocessing techniques, feature representation, sentiment classification levels, and models, and they use different datasets. Such variations are worthy of attention and monitoring. Despite the importance of SA in hospitality and tourism, review studies identifying gaps and suggesting future research directions are limited. This article introduces a systematic literature review to label and discuss state-of-the-art studies that deal with SA for hotel reviews.

Publisher

Association for Computing Machinery (ACM)

Subject

General Computer Science,Theoretical Computer Science

Cited by 6 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Customer perceptions on open banking apps: Insights using Structural topic modeling;Journal of Retailing and Consumer Services;2024-11

2. Customer experience and customer satisfaction: assessing links and themes in the hotel industry;Revista de Estudios Empresariales. Segunda Época;2024-07-30

3. Sentiments analysis for intelligent customer service dialogue using hybrid word embedding and stacking ensemble;Soft Computing;2024-07-12

4. Machine Learning and Sentiment Analysis;Advances in Marketing, Customer Relationship Management, and E-Services;2024-04-19

5. Customer Feedback and Sentiment Analysis for Hotel Services;2024 International Conference on Distributed Computing and Optimization Techniques (ICDCOT);2024-03-15

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