At present, most of the rumor detection methods take the content of Weibo text as the main target of rumor detection. This study uses user information and Weibo text as the target to detect Weibo rumors, and the focus is on user information. A rumor detection model based on Bert [1] combined with DPCNN [2] method is proposed, which can process Chinese data more conveniently, extract the characteristics of user information more accurately, and introduce the evaluation standard as the final evaluation index. Finally, a microblog rumor detection system based on user information is constructed to make the rumor detection more accurate.
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