{"url":"/dataset/acos","name":"ACOS","full_name":"Aspect Category Opinion Sentiment","description_markdown":"Most of the aspect based sentiment analysis research aims at identifying the sentiment polarities toward some explicit aspect terms while ignores implicit aspects in text. To capture both explicit and implicit aspects, we focus on aspect-category based sentiment analysis, which involves joint aspect category detection and category-oriented sentiment classification. However, currently only a few simple studies have focused on this problem. The shortcomings in the way they defined the task make their approaches difficult to effectively learn the inner-relations between categories and the inter-relations between categories and sentiments. In this work, we re-formalize the task as a category-sentiment hierarchy prediction problem, which contains a hierarchy output structure to first identify multiple aspect categories in a piece of text, and then predict the sentiment for each of the identified categories. Specifically, we propose a Hierarchical Graph Convolutional Network (Hier-GCN), where a lower-level GCN is to model the inner-relations among multiple categories, and the higher-level GCN is to capture the inter-relations between aspect categories and sentiments. Extensive evaluations demonstrate that our hierarchy output structure is superior over existing ones, and the Hier-GCN model can consistently achieve the best results on four benchmarks.","description_withheld":null,"homepage":"","introduced_date":"2020-12-01","introduced_date_note":null,"introduced_by":{"paper":"/paper/aspect-category-based-sentiment-analysis-with","title":"Aspect-Category based Sentiment Analysis with Hierarchical Graph Convolutional Network","first_author":"Hongjie Cai","url":null},"license":null,"modalities":[],"tasks":[{"name":"Aspect-Based Sentiment Analysis (ABSA)","url":"/task/aspect-based-sentiment-analysis","datasets_with_task":"/datasets/task/aspect-based-sentiment-analysis"}],"languages":[],"variants":["ACOS"],"data_loaders":[],"num_papers_in_archive":11,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/aspect-based-sentiment-analysis-absa-on-acos","task":"Aspect-Based Sentiment Analysis (ABSA)","dataset_variant":"ACOS","rows":9,"metrics":["F1 (Laptop)","F1 (Restaurant)"],"first_row_in_archive_order":{"model":"MvP","paper":"/paper/mvp-multi-view-prompting-improves-aspect","metrics":{"F1 (Laptop)":"43.92","F1 (Restaurant)":"61.54"},"code_links":[{"title":"ZubinGou/multi-view-prompting","url":"https://github.com/ZubinGou/multi-view-prompting"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/mvp-multi-view-prompting-improves-aspect","title":"MvP: Multi-view Prompting Improves Aspect Sentiment Tuple Prediction","date":"2023-05-22","rows_on_this_dataset":4,"code_links":1,"syntology":null},{"paper":"/paper/unifiedabsa-a-unified-absa-framework-based-on","title":"UnifiedABSA: A Unified ABSA Framework Based on Multi-task Instruction Tuning","date":"2022-11-20","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/improving-aspect-sentiment-quad-prediction","title":"Improving Aspect Sentiment Quad Prediction via Template-Order Data Augmentation","date":"2022-10-19","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/aspect-sentiment-quad-prediction-as","title":"Aspect Sentiment Quad Prediction as Paraphrase Generation","date":"2021-10-02","rows_on_this_dataset":2,"code_links":1,"syntology":null},{"paper":"/paper/aspect-category-opinion-sentiment-quadruple","title":"Aspect-Category-Opinion-Sentiment Quadruple Extraction with Implicit Aspects and Opinions","date":"2021-08-01","rows_on_this_dataset":1,"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."}