Rumor has it: Identifying Misinformation in Microblogs

摘要: A rumor is commonly defined as a statement whose true value unverifiable. Rumors may spread misinformation (false information) or disinformation (deliberately false on network of people. Identifying rumors crucial in online social media where large amounts information are easily across by sources with unverified authority. In this paper, we address the problem detection microblogs and explore effectiveness 3 categories features: content-based, network-based, microblog-specific memes for correctly identifying rumors. Moreover, show how these features also effective disinformers, users who endorse further help it to spread. We perform our experiments more than 10,000 manually annotated tweets collected from Twitter retrieval model achieves 0.95 Mean Average Precision (MAP). Finally, believe that dataset first large-scale detection. It can open new dimensions analyzing other aspects microblog conversations.