MuMiN is a misinformation graph dataset containing rich social media data (tweets, replies, users, images, articles, hashtags), spanning 21 million tweets belonging to 26 thousand Twitter threads, each of which have been semantically linked to 13 thousand fact-checked claims across dozens of topics, events and domains, in 41 different languages, spanning more than a decade.
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The task addresses the problem of the appearance and propagation of posts that share misleading multimedia content (images or video). In the context of the task, different types of misleading use are considered:
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