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

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

The gastronomy tourism industry plays an important role in boosting local economies, enhancing the travel experience, and preserving culinary traditions unique to specific places. In this context, comprehending customer sentiments is of paramount importance for business decision-making, menu choice...

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Bibliographic Details
Main Authors: Mohd Norhisham Razali, Syaifulnizam Abdul Manaf, Rozita Binti Hanapi, Mohd Rafiz Salji, Lee Wen Chiat, Kashif Nisar
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Business analytics
machine learning
sentiment analysis
tourism industry
data visualization
Online Access:https://ieeexplore.ieee.org/document/10422746/

Internet

https://ieeexplore.ieee.org/document/10422746/

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