A Amazon dataset of 1,396,896 QA pairs across 21 categories, collected by Wan and McAuley via Amazon API. Each record contains question, answer, question type, answer type, ASIN, timestamp. Comprehensive Amazon product Q&A data across 21 categories. Suitable for question answering, sentiment analysis, product understanding, conversational AI. The record count covers the single-answer files (qa_*.json.gz, one question and answer per line). The package also holds the multiple-answer release used in Wan and McAuley's ICDM 2016 paper (icdm/QA_*.json.gz, 17 categories: 172,617 products, 1,025,628 questions and 4,019,744 answers, with asker and answerer IDs and helpfulness votes), and McAuley's data page (index.html). Both are written as Python literals, not strict JSON (read them with ast.literal_eval).
A Amazon dataset of 146,891 QA pairs in Sports & Outdoors, 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 Sports & Outdoors. Suitable for question answering, sentiment analysis, product understanding, conversational AI.
A Amazon dataset of 85,865 QA pairs in Cell Phones & Accessories, 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 Cell Phones & Accessories. Suitable for question answering, sentiment analysis, product understanding, conversational AI.
A Amazon dataset of 80,496 QA pairs in Health & Personal Care, 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 Health & Personal Care. Suitable for question answering, sentiment analysis, product understanding, conversational AI.
A Amazon dataset of 43,608 QA pairs in Office Products, 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 Office Products. Suitable for question answering, sentiment analysis, product understanding, conversational AI.
A Amazon dataset of 21,262 QA pairs in Arts Crafts & Sewing, 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 Arts Crafts & Sewing. Suitable for question answering, sentiment analysis, product understanding, conversational AI.
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