{"url":"/dataset/tbcov","name":"TBCOV","full_name":null,"description_markdown":"TBCOV is a large-scale Twitter dataset comprising more than two billion multilingual tweets related to the COVID-19 pandemic collected worldwide over a continuous period of more than one year. Several state-of-the-art deep learning models are used to enrich the data with important attributes, including sentiment labels, named-entities (e.g., mentions of persons, organizations, locations), user types, and gender information. A geotagging method is proposed to assign country, state, county, and city information to tweets, enabling a myriad of data analysis tasks to understand real-world issues.\r\n\r\nDescription from: [TBCOV: Two Billion Multilingual COVID-19 Tweets with Sentiment, Entity, Geo, and Gender Labels](https://arxiv.org/pdf/2110.03664v1.pdf)\r\n\r\nImage source: [https://arxiv.org/pdf/2110.03664v1.pdf](https://arxiv.org/pdf/2110.03664v1.pdf)","description_withheld":null,"homepage":"https://crisisnlp.qcri.org/tbcov","introduced_date":"2021-10-04","introduced_date_note":null,"introduced_by":{"paper":"/paper/tbcov-two-billion-multilingual-covid-19","title":"TBCOV: Two Billion Multilingual COVID-19 Tweets with Sentiment, Entity, Geo, and Gender Labels","first_author":"Muhammad Imran","url":null},"license":{"name":"Unknown","url":null},"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Sentiment Analysis","url":"/task/sentiment-analysis","datasets_with_task":"/datasets/task/sentiment-analysis"}],"languages":[],"variants":["TBCOV"],"data_loaders":[{"repo":"https://github.com/crisiscomputing/tbcov","url":"https://github.com/crisiscomputing/tbcov","frameworks":[]}],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"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."}