A Method of Fast Rumors Identification on Microblog

Abstract

Microblog realizes the real-time sharing of information whereas there is a great deal of false information at the same time. The widely propagation of rumors on microblog may give rise to public panic, the trust crisis of Internet and even endanger national security. Given the overflow problem of rumors, this paper proposes a method of fast identification of rumors extracting the corresponding eigenvector of each microblog according to the characteristics based on content and propagation digging from rumors on microblog. The similarity degree is measured by cosine theorem. Recognition results can effectively help people identify rumors better.