Real-Time News Certification System on Sina Weibo
Real-Time News Certification System on Sina Weibo Xing Zhou1;2, Juan Cao1, Zhiwei Jin1;2,Fei Xie3,Yu Su3,Junqiang Zhang1;2,Dafeng Chu3, ,Xuehui Cao3 1Key Laboratory of Intelligent Information Processing of Chinese Academy of Sciences (CAS) Institute of Computing Technology, Beijing, China 2University of Chinese Academy of Sciences, Beijing, China 3Xinhua News Agency, Beijing, China {zhouxing,caojuan,jinzhiwei,zhangjunqiang}@ict.ac.cn {xiefei,suyu,chudafeng,caoxuehui}@xinhua.org ABSTRACT There are many works has been done on rumor detec- In this paper, we propose a novel framework for real-time tion. Storyful[2] is the world's first social media news agency, news certification. Traditional methods detect rumors on which aims to discover breaking news and verify them at the message-level and analyze the credibility of one tweet. How- first time. Sina Weibo has an official service platform1 that ever, in most occasions, we only remember the keywords encourage users to report fake news and these news will be of an event and it's hard for us to completely describe an judged by official committee members. Undoubtedly, with- event in a tweet. Based on the keywords of an event, we out proper domain knowledge, people can hardly distinguish gather related microblogs through a distributed data acqui- between fake news and other messages. The huge amount sition system which solves the real-time processing need- of microblogs also make it impossible to identify rumors by s. Then, we build an ensemble model that combine user- humans. based, propagation-based and content-based model. The Recently, many researches has been devoted to automatic experiments show that our system can give a response at rumor detection on social media.
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