Expert Finding for Microblog Misinformation Identification
نویسندگان
چکیده
The growth of social media provides a convenient communication scheme for people, but at the same time it becomes a hotbed of misinformation. The wide spread of misinformation over social media is injurious to public interest. We design a framework, which integrates collective intelligence and machine intelligence, to help identify misinformation. The basic idea is: (1) automatically index the expertise of users according to their microblog contents; and (2) match the experts with given suspected misinformation. By sending the suspected misinformation to appropriate experts, we can collect the assessments of experts to judge the credibility of information, and help refute misinformation. In this paper, we focus on expert finding for misinformation identification. We propose a tag-based method to index the expertise of microblog users with social tags. Experiments on a real world dataset demonstrate the effectiveness of our method for expert finding with respect to misinformation identification in microblogs. TITLE AND ABSTRACT IN CHINESE ¡ÆØ¢&E£O ;[uy 3Ǒ<Jø B| 6a Ó§ ¬xNǑ¤ǑØ¢&ED §K"Ø ¢&E3 ¬xN¥ 2DÂòéú | E¤3"ùp§·JÑnÜ|^+N UÚÅìUÏ£OØ¢&E§Ä g ́μ£1¤âÆ^r )SNgÄ©ÛÚ ¢Ú^r ;¶£2¤gÄò Ø¢&EA ;[ "ÏLòØ¢&Eux Ü· ;[§·±Â8;[é&E&5 μ §Ï£OØ¢&EÚ8" Ø©òÌ&?¡Ø¢&E£O ;[uy ̄K"·æ^ÄuI\ {5¢ÚÆ ^r ;"3ý¢êâþ ¢ L2§· {±k ?1Æ;[uy^uØ¢ &E£O"
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