A Amazon.com movie product pages dataset of 7,911,696 movie reviews spanning 1997 to 2012, collected by McAuley & Leskovec via Amazon product review pages (2013). Each record contains product ID, reviewer user ID, reviewer profile name, helpfulness votes (numerator/denominator), star rating (1-5), Unix timestamp, review summary, and full review text. One of the largest Amazon review datasets publicly available — 8 million movie reviews with full text, helpfulness votes, and star ratings spanning 15 years of Amazon movie reviews.. Suitable for sentiment analysis, review helpfulness prediction, recommendation systems, user expertise modeling, longitudinal review behavior analysis.
A Amazon dataset of 184,439 QA pairs in Home & Kitchen, collected by Wan and McAuley via Amazon API. Each record contains question, answer, question type, answer type, ASIN, timestamp. Amazon product Q&A data for Home & Kitchen. Suitable for question answering, sentiment analysis, product understanding, conversational AI.
A Amazon dataset of 101,088 QA pairs in Tools & Home Improvement, collected by Wan and McAuley via Amazon API. Each record contains question, answer, question type, answer type, ASIN, timestamp. Amazon product Q&A data for Tools & Home Improvement. Suitable for question answering, sentiment analysis, product understanding, conversational AI.
A Amazon dataset of 89,923 QA pairs in Automotive, collected by Wan and McAuley via Amazon API. Each record contains question, answer, question type, answer type, ASIN, timestamp. Amazon product Q&A data for Automotive. Suitable for question answering, sentiment analysis, product understanding, conversational AI.
A Amazon dataset of 59,595 QA pairs in Patio Lawn & Garden, collected by Wan and McAuley via Amazon API. Each record contains question, answer, question type, answer type, ASIN, timestamp. Amazon product Q&A data for Patio Lawn & Garden. Suitable for question answering, sentiment analysis, product understanding, conversational AI.
A Amazon dataset of 22,068 QA pairs in Clothing Shoes & Jewelry, collected by Wan and McAuley via Amazon API. Each record contains question, answer, question type, answer type, ASIN, timestamp. Amazon product Q&A data for Clothing Shoes & Jewelry. Suitable for question answering, sentiment analysis, product understanding, conversational AI.
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