{"url":"/dataset/twitter-comms","name":"Twitter-COMMs","full_name":"Twitter-COMMs","description_markdown":"Detecting out-of-context media, such as \"mis-captioned\" images on Twitter, is a relevant problem, especially in domains of high public significance. Twitter-COMMs is a large-scale multimodal dataset with 884k tweets relevant to the topics of Climate Change, COVID-19, and Military Vehicles. This dataset can be used to develop methods to detect misinformation on social media platforms related to these three topics.","description_withheld":null,"homepage":"https://github.com/GiscardBiamby/Twitter-COMMs","introduced_date":"2021-12-16","introduced_date_note":null,"introduced_by":{"paper":"/paper/twitter-comms-detecting-climate-covid-and","title":"Twitter-COMMs: Detecting Climate, COVID, and Military Multimodal Misinformation","first_author":"Giscard Biamby","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Misinformation","url":"/task/misinformation","datasets_with_task":"/datasets/task/misinformation"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["Twitter-COMMs"],"data_loaders":[],"num_papers_in_archive":3,"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."}