Enhancing Minority Sentiment Classification in Gastronomy Tourism: A Hybrid Sentiment Analysis Framework With Data Augmentation, Feature Engineering and Business Intelligence-Reference-Cited by-同舟云学术

Enhancing Minority Sentiment Classification in Gastronomy Tourism: A Hybrid Sentiment Analysis Framework With Data Augmentation, Feature Engineering and Business Intelligence

Published:2024 Issue: Volume:12 Page:49387-49407
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Razali Mohd Norhisham¹^ORCID,Manaf Syaifulnizam Abdul²^ORCID,Hanapi Rozita Binti¹,Salji Mohd Rafiz³^ORCID,Chiat Lee Wen¹,Nisar Kashif⁴

Affiliation:

1. Faculty Business and Management, Universiti Teknologi MARA Sarawak, Kota Samarahan, Sarawak, Malaysia

2. Faculty of Computer Science and Information Technology, Universiti Putra Malaysia, Serdang, Malaysia

3. College of Computing, Informatics and Mathematics, Universiti Teknologi MARA Sarawak, Kota Samarahan, Sarawak, Malaysia

4. Swinburne University of Technology, Sydney, Australia

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6287639/10380310/10422746.pdf?arnumber=10422746

Reference31 articles.

1. Toward Text Data Augmentation for Sentiment Analysis

2. Sentiment Analysis of Customer Reviews of Food Delivery Services Using Deep Learning and Explainable Artificial Intelligence: Systematic Review

3. The Impact of Features Extraction on the Sentiment Analysis

4. Evaluation of destination image among foreign tourists: The case of Sarawak;Alam,2019

5. Arabic Sentiment Analysis of Eateries’ Reviews: Qassim region Case study

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