{"url":"/dataset/amasum","name":"AmaSum","full_name":null,"description_markdown":"AmaSum is the largest abstractive opinion summarization dataset, consisting of more than 33,000 human-written summaries for Amazon products. Each summary is paired, on average, with more than 320 customer reviews. Summaries consist of verdicts, pros, and cons, see the example below.","description_withheld":null,"homepage":"https://github.com/abrazinskas/SelSum","introduced_date":"2021-09-09","introduced_date_note":null,"introduced_by":{"paper":"/paper/learning-opinion-summarizers-by-selecting","title":"Learning Opinion Summarizers by Selecting Informative Reviews","first_author":"Arthur Bražinskas","url":null},"license":null,"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Unsupervised Opinion Summarization","url":"/task/unsupervised-opinion-summarization","datasets_with_task":"/datasets/task/unsupervised-opinion-summarization"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["AmaSum"],"data_loaders":[],"num_papers_in_archive":8,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}