{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/emotxt-a-toolkit-for-emotion-recognition-from","title":"EmoTxt: A Toolkit for Emotion Recognition from Text","arxiv_id":"1708.03892","date":"2017-08-13","proceeding":null,"authors":["Fabio Calefato","Filippo Lanubile","Nicole Novielli"],"abstract":"We present EmoTxt, a toolkit for emotion recognition from text, trained and\ntested on a gold standard of about 9K question, answers, and comments from\nonline interactions. We provide empirical evidence of the performance of\nEmoTxt. To the best of our knowledge, EmoTxt is the first open-source toolkit\nsupporting both emotion recognition from text and training of custom emotion\nclassification models.","url_abs":"http://arxiv.org/abs/1708.03892v2","url_pdf":"http://arxiv.org/pdf/1708.03892v2.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"emotxt-a-toolkit-for-emotion-recognition-from","repo_url":"https://github.com/brandonserna/sentiment2emoji","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null},{"paper_slug":"emotxt-a-toolkit-for-emotion-recognition-from","repo_url":"https://github.com/collab-uniba/Emotion_and_Polarity_SO","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"emotion-classification","task_name":"Emotion Classification"},{"task_slug":"emotion-recognition","task_name":"Emotion Recognition"},{"task_slug":"classification","task_name":"General Classification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}