{"url":"/dataset/ch-sims","name":"CH-SIMS","full_name":"CH-SIMS","description_markdown":"CH-SIMS is a Chinese single- and multimodal sentiment analysis dataset which contains 2,281 refined video segments in the wild with both multimodal and independent unimodal annotations. It allows researchers to study the interaction between modalities or use independent unimodal annotations for unimodal sentiment analysis.\r\n\r\nSource: [CH-SIMS: A Chinese Multimodal Sentiment Analysis Dataset with Fine-grained Annotations of Modality](https://www.aclweb.org/anthology/2020.acl-main.343.pdf)","description_withheld":null,"homepage":"https://github.com/thuiar/MMSA","introduced_date":"2020-07-01","introduced_date_note":null,"introduced_by":{"paper":"/paper/ch-sims-a-chinese-multimodal-sentiment","title":"CH-SIMS: A Chinese Multimodal Sentiment Analysis Dataset with Fine-grained Annotation of Modality","first_author":"Wenmeng Yu","url":null},"license":null,"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Sentiment Analysis","url":"/task/sentiment-analysis","datasets_with_task":"/datasets/task/sentiment-analysis"},{"name":"Multi-Task Learning","url":"/task/multi-task-learning","datasets_with_task":"/datasets/task/multi-task-learning"},{"name":"Multimodal Sentiment Analysis","url":"/task/multimodal-sentiment-analysis","datasets_with_task":"/datasets/task/multimodal-sentiment-analysis"}],"languages":[{"name":"Chinese","url":"/datasets/language/chinese"}],"variants":["CH-SIMS"],"data_loaders":[{"repo":"https://github.com/thuiar/MMSA","url":"https://github.com/thuiar/MMSA","frameworks":["pytorch"]}],"num_papers_in_archive":25,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/multimodal-sentiment-analysis-on-ch-sims","task":"Multimodal Sentiment Analysis","dataset_variant":"CH-SIMS","rows":2,"metrics":["F1","MAE","CORR","Acc-2","Acc-3","Acc-5"],"first_row_in_archive_order":{"model":"MMML","paper":"/paper/multi-modality-multi-loss-fusion-network","metrics":{"CORR":"73.26","F1":"82.9","MAE":"0.332"},"code_links":[{"title":"zehuiwu/MMML","url":"https://github.com/zehuiwu/MMML"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/learning-language-guided-adaptive-hyper","title":"Learning Language-guided Adaptive Hyper-modality Representation for Multimodal Sentiment Analysis","date":"2023-10-09","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/multi-modality-multi-loss-fusion-network","title":"Multimodal Multi-loss Fusion Network for Sentiment Analysis","date":"2023-08-01","rows_on_this_dataset":1,"code_links":1,"syntology":null}],"syntology_totals":{"read_at":"2026-09-25T09:33:49+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."}