TripAdvisor Hotel Reviews Dataset — Discover Insights from Hotel Data

TripAdvisor Hotel Reviews Dataset is a large collection of user reviews, ratings, and metadata collected from TripAdvisor. It captures real guest experiences about hotels, rooms, service, location, and pricing. 

For data analysts, NLP researchers, and AI practitioners, this hotel review dataset is a valuable resource for sentiment analysis, trend detection, and customer feedback research.

Why is this dataset valuable for AI and NLP?

• Real user language: Reviews include short comments, long narratives, slang, and structured ratings.
  
• Sentiment labels: Star ratings provide a natural label for sentiment analysis.
  
• Scale: Large volumes allow robust model training and evaluation.
  
• Domain-specific insights: Hotel-specific terminology improves model understanding in travel and hospitality contexts.
  

What fields are included in this dataset?

Crawl Feeds provides a structured and cleaned dataset that includes:

• Review text (raw and cleaned)
• Star rating (1–5)
• Review title
• Review date and timestamp
• Hotel name and location
• Review language and helpfulness votes

How can I use this dataset for sentiment analysis?

• Train supervised classifiers (e.g., BERT, RoBERTa) using star ratings as labels.
  
• Apply lexicon-based approaches for quick sentiment scoring.
  
• Detect trends by comparing sentiment over time or across locations.
  Example workflow: clean text → tokenize → train model → evaluate accuracy → analyze errors by location or hotel type.
  

How can this dataset improve customer insights?

• Trend detection: Identify rising complaints or praise, such as cleanliness or amenities.
  
• Review summarization: Condense multiple reviews into key pros and cons.
  
• Feature extraction: Detect recurring topics like breakfast quality, staff friendliness, or room comfort.
  
• Recommendation systems: Combine ratings and text signals to suggest hotels to new customers.
  

Where can I download hotel review datasets?

Crawl Feeds is a trusted source for TripAdvisor hotel datasets. They provide structured CSV or JSON files that are ready for analysis, saving time on cleaning and formatting.

Why choose Crawl Feeds hotel datasets?

• Cleaned and standardised fields for easy processing.
  
• Consistent structure across multiple hotels.
  
• Large volume suitable for sentiment analysis, text mining, and recommendation modeling.
  
• Ready for AI and NLP workflows without heavy preprocessing.
  

How to Prepare the Dataset for Analysis?

• Deduplicate reviews and filter spam.
  
• Normalize dates and timestamps for temporal analysis.
  
• Balance sentiment classes for classification tasks.
  
• Split data into training and test sets for model evaluation.
  

Common use cases for the TripAdvisor Hotel Reviews Dataset:

• Sentiment analysis: Detect positive, neutral, or negative reviews.
  
• Text mining: Identify patterns and topics across reviews.
  
• Customer feedback analysis: Understand key pain points or highlights.
  
• Competitive benchmarking: Compare sentiment trends across hotels or locations.
  
• Recommendation engines: Enhance booking suggestions using review insights.
  

Final Thoughts

TripAdvisor Hotel Reviews Dataset from Crawl Feeds is a must-have resource for anyone working on hospitality data, sentiment analysis, or customer feedback research. With structured, cleaned, and ready-to-use reviews, analysts and AI practitioners can save time and focus on deriving actionable insights.

Explore the Crawl Feeds TripAdvisor Hotel Reviews Dataset today. Download the dataset to start analysing hotel sentiment, uncover trends, and build smarter travel and hospitality solutions.