{"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/idsou-at-wnut-2020-task-2-identification-of","title":"IDSOU at WNUT-2020 Task 2: Identification of Informative COVID-19 English Tweets","arxiv_id":null,"date":"2020-11-01","proceeding":"EMNLP (WNUT) 2020 11","authors":["Sora Ohashi","Tomoyuki Kajiwara","Chenhui Chu","Noriko Takemura","Yuta Nakashima","Hajime Nagahara"],"abstract":"We introduce the IDSOU submission for the WNUT-2020 task 2: identification of informative COVID-19 English Tweets. Our system is an ensemble of pre-trained language models such as BERT. We ranked 16th in the F1 score.","url_abs":"https://aclanthology.org/2020.wnut-1.62","url_pdf":"https://aclanthology.org/2020.wnut-1.62.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":"idsou-at-wnut-2020-task-2-identification-of","repo_url":"https://github.com/VinAIResearch/COVID19Tweet","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[{"task_slug":"task-2","task_name":"Task 2"}],"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}