{"url":"/dataset/fabsa","name":"FABSA","full_name":"An aspect-based sentiment analysis dataset of Customer Feedback reviews","description_markdown":"FABSA, An aspect-based sentiment analysis dataset in the Customer Feedback space (Trustpilot, Google Play and Apple Store reviews).\r\n\r\nA professionally annotated dataset released by Chattermill AI, with 8 years of experience in leveraging advanced ML analytics in the customer feedback space for high-profile clients such as Amazon and Uber.\r\n\r\nTwo annotators possess extensive experience in developing human-labeled ABSA datasets for commercial companies, while the third annotator holds a PhD in computational linguistics.\r\n\r\nThere has been a lack of high-quality ABSA datasets covering broad domains and addressing real-world applications. Academic progress has been confined to benchmarking on domain-specific, toy datasets such as restaurants and laptops, which are limited in size (e.g., SemEval Task ABSA or SentiHood).\r\n\r\nThis dataset is part of the FABSA paper, and we release it hoping to advance academic progress as tools for ingesting and analyzing customer feedback at scale improve significantly, yet evaluation datasets continue to lag. FABSA is a new, large-scale, multi-domain ABSA dataset of feedback reviews, consisting of approximately 10,500 reviews spanning 10 domains (Fashion, Consulting, Travel Booking, Ride-hailing, Banking, Trading, Streaming, Price Comparison, Information Technology, and Groceries).\r\n\r\n[Academic Paper](https://www.sciencedirect.com/science/article/pii/S0925231223009906)\r\n\r\n```\r\n@article{KONTONATSIOS2023126867,\r\ntitle = {FABSA: An aspect-based sentiment analysis dataset of user reviews},\r\njournal = {Neurocomputing},\r\nvolume = {562},\r\npages = {126867},\r\nyear = {2023},\r\nissn = {0925-2312},\r\ndoi = {https://doi.org/10.1016/j.neucom.2023.126867},\r\nurl = {https://www.sciencedirect.com/science/article/pii/S0925231223009906},\r\nauthor = {Georgios Kontonatsios and Jordan Clive and Georgia Harrison and Thomas Metcalfe and Patrycja Sliwiak and Hassan Tahir and Aji Ghose},\r\nkeywords = {ABSA, Multi-domain dataset, Deep learning},\r\n}```","description_withheld":null,"homepage":"https://huggingface.co/datasets/jordiclive/FABSA","introduced_date":"2023-12-28","introduced_date_note":null,"introduced_by":null,"license":{"name":"Creative Commons  Attribution BY 4.0 Deed","url":"https://creativecommons.org/licenses/by/4.0/deed.en"},"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Aspect-Based Sentiment Analysis (ABSA)","url":"/task/aspect-based-sentiment-analysis","datasets_with_task":"/datasets/task/aspect-based-sentiment-analysis"},{"name":"Aspect Category Detection","url":"/task/aspect-category-detection","datasets_with_task":"/datasets/task/aspect-category-detection"},{"name":"Aspect-Based Sentiment Analysis","url":"/task/aspect-based-sentiment-analysis-1","datasets_with_task":"/datasets/task/aspect-based-sentiment-analysis-1"},{"name":"Aspect Category Polarity","url":"/task/aspect-category-polarity","datasets_with_task":"/datasets/task/aspect-category-polarity"},{"name":"Aspect Category Sentiment Analysis","url":"/task/aspect-category-sentiment-analysis","datasets_with_task":"/datasets/task/aspect-category-sentiment-analysis"},{"name":"Hidden Aspect Detection","url":"/task/hidden-aspect-detection","datasets_with_task":"/datasets/task/hidden-aspect-detection"},{"name":"Latent Aspect Detection","url":"/task/latent-aspect-detection","datasets_with_task":"/datasets/task/latent-aspect-detection"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["FABSA"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/aspect-based-sentiment-analysis-absa-on-fabsa","task":"Aspect-Based Sentiment Analysis (ABSA)","dataset_variant":"FABSA","rows":4,"metrics":["F1 (%)"],"first_row_in_archive_order":{"model":"DeBERTa-pair-large","paper":"/paper/fabsa-an-aspect-based-sentiment-analysis","metrics":{"F1 (%)":"80.9"},"code_links":[{"title":"jordiclive/FABSA","url":"https://huggingface.co/datasets/jordiclive/FABSA"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/aspect-category-sentiment-analysis-on-fabsa","task":"Aspect Category Sentiment Analysis","dataset_variant":"FABSA","rows":4,"metrics":["F1 (%)"],"first_row_in_archive_order":{"model":"DeBERTa-pair-large","paper":"/paper/fabsa-an-aspect-based-sentiment-analysis","metrics":{"F1 (%)":"80.9"},"code_links":[{"title":"jordiclive/FABSA","url":"https://huggingface.co/datasets/jordiclive/FABSA"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/fabsa-an-aspect-based-sentiment-analysis","title":"FABSA: An aspect-based sentiment analysis dataset of user reviews","date":"2023-12-28","rows_on_this_dataset":8,"code_links":1,"syntology":null}],"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."}