Interpretable rumor detection in microblogs by attending to user interactions
national conference on artificial intelligence, 2020.
Abstract:
We address rumor detection by learning to differentiate between the community's response to real and fake claims in microblogs. Existing state-of-the-art models are based on tree models that model conversational trees. However, in social media, a user posting a reply might be replying to the entire thread rather than to a specific user....More
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