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In an era of burgeoning online reviews, the hospitality industry faces a digital metamorphosis in understanding customer sentiments. This study explores the nuances of sentiment analysis, a critical natural language processing (NLP) method, utilizing reviews of Taj Hotels from various parts of India. Using the extensive SentiWordNet lexicon, sentiment polarities are measured using NLP methods. By using this perspective, our research reveals complex feelings, tastes, and geographical differences, providing useful information for improving visitor experiences in the Taj Hotel sector. Sentiment analysis techniques, such as word cloud generation, are applied to enable a detailed understanding of user sentiment on TripAdvisor. Our study makes a unique contribution to the improvement of sentiment analysis techniques by offering focused tactics for localized service modification in the hotel sector.

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Exploring Sentiment Variations in Hotel Industry on TripAdvisor Reviews Across Diverse Indian Regions Using Machine Learning Approach

  • 会议论文

  • 发表日期：

    2025年

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  • Sainah Sreeram,
  • Ananya Tyagi,
  • Sonakshi Vij

摘要

In an era of burgeoning online reviews, the hospitality industry faces a digital metamorphosis in understanding customer sentiments. This study explores the nuances of sentiment analysis, a critical natural language processing (NLP) method, utilizing reviews of Taj Hotels from various parts of India. Using the extensive SentiWordNet lexicon, sentiment polarities are measured using NLP methods. By using this perspective, our research reveals complex feelings, tastes, and geographical differences, providing useful information for improving visitor experiences in the Taj Hotel sector. Sentiment analysis techniques, such as word cloud generation, are applied to enable a detailed understanding of user sentiment on TripAdvisor. Our study makes a unique contribution to the improvement of sentiment analysis techniques by offering focused tactics for localized service modification in the hotel sector.