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Amazon Food Product Reviews & Ratings
E-commerce & Online Transactions
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About
The Amazon Food Products Dataset is a large-scale collection of product listings, reviews, and metadata sourced from Amazon. This dataset is valuable for understanding consumer behaviour, analyzing product trends, and training machine learning models for recommendation systems and sentiment analysis. It includes various categories, providing insights into customer preferences, product ratings, and review sentiments.
Dataset Features
Each record in the dataset contains the following key fields:
- ProductId: Unique identifier for each product.
- UserId: Unique identifier for the reviewer.
- ProfileName: Display the name of the reviewer.
- HelpfulnessNumerator: Number of users who found the review helpful.
- HelpfulnessDenominator: Total number of users who rated the review’s helpfulness.
- Score: Product rating (1 to 5 stars).
- Time: Unix timestamp of the review.
- Summary: Short summary of the review.
- Text: Full text of the review.
Distribution
- Data Volume: 568454 rows and 9 columns.
- Format: CSV.
- Structure: Tabular format with numerical, categorical, and text data.
Usage
This dataset is ideal for a variety of applications:
- Sentiment Analysis: Training NLP models to predict sentiment based on reviews.
- Product Recommendation Systems: Building collaborative filtering models.
- Trend Analysis: Identifying popular products and customer preferences.
- Fake Review Detection: Detecting anomalous patterns in review behaviours.
Coverage
- Geographic Coverage: Global.
- Time Range: Multi-year dataset (over 10 years of reviews).
- Demographics: General Amazon shoppers; includes various age groups and customer segments.
License
CC0
Who Can Use It
- Data Scientists: For building machine learning models.
- Researchers: For academic analysis of customer behaviour.
- Businesses: For market insights and customer sentiment analysis.
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