{"url":"/dataset/emotionlines","name":"EmotionLines","full_name":"EmotionLines","description_markdown":"**EmotionLines** contains a total of 29245 labeled utterances from 2000 dialogues. Each utterance in dialogues is labeled with one of seven emotions, six Ekman’s basic emotions plus the neutral emotion. Each labeling was accomplished by 5 workers, and for each utterance in a label, the emotion category with the highest votes was set as the label of the utterance. Those utterances voted as more than two different emotions were put into the non-neutral category. Therefore the dataset has a total of 8 types of emotion labels, anger, disgust, fear, happiness, sadness, surprise, neutral, and non-neutral.\r\n\r\nSource: [Bridging Dialogue Generation and Facial Expression Synthesis](https://arxiv.org/abs/1905.11240)\r\nImage Source: [https://arxiv.org/pdf/1802.08379.pdf](https://arxiv.org/pdf/1802.08379.pdf)","description_withheld":null,"homepage":"http://doraemon.iis.sinica.edu.tw/emotionlines/download.html","introduced_date":"2018-01-01","introduced_date_note":null,"introduced_by":{"paper":"/paper/emotionlines-an-emotion-corpus-of-multi-party","title":"EmotionLines: An Emotion Corpus of Multi-Party Conversations","first_author":"Sheng-Yeh Chen","url":null},"license":{"name":"CC BY-NC-ND","url":"https://creativecommons.org/licenses/by-nc-nd/4.0/"},"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Language Modelling","url":"/task/language-modelling","datasets_with_task":"/datasets/task/language-modelling"},{"name":"Emotion Recognition","url":"/task/emotion-recognition","datasets_with_task":"/datasets/task/emotion-recognition"},{"name":"Emotion Recognition in Conversation","url":"/task/emotion-recognition-in-conversation","datasets_with_task":"/datasets/task/emotion-recognition-in-conversation"},{"name":"Emotion Classification","url":"/task/emotion-classification","datasets_with_task":"/datasets/task/emotion-classification"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["EmotionPush","EmotionLines"],"data_loaders":[],"num_papers_in_archive":44,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/emotion-recognition-in-conversation-on-5","task":"Emotion Recognition in Conversation","dataset_variant":"EmotionPush","rows":1,"metrics":["Unweighted Accuracy","Weighted Accuracy"],"first_row_in_archive_order":{"model":"HiTransformer-s","paper":"/paper/hierarchical-transformer-network-for","metrics":{"Unweighted Accuracy":"63.03","Weighted Accuracy":"86.92"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/hierarchical-transformer-network-for","title":"Hierarchical Transformer Network for Utterance-level Emotion Recognition","date":"2020-02-18","rows_on_this_dataset":1,"code_links":0,"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."}