document: Information credibility on twitter We analyze the information credibility of news propagated through Twitter , a popular microblogging service . Previous research has shown that most of the messages posted on Twitter are truthful , but the service is also used to spread misinformation and false rumors , often unintentionally . On this paper we focus on automatic methods for assessing the credibility of a given set of tweets . Specifically , we analyze microblog postings related to `` trending '' topics , and classify them as credible or not credible , based on features extracted from them . We use features from users ' posting and re-posting ( `` re-tweeting '' ) behavior , from the text of the posts , and from citations to external sources . We evaluate our methods using a significant number of human assessments about the credibility of items on a recent sample of Twitter postings . Our results shows that there are measurable differences in the way messages propagate , that can be used to classify them automatically as credible or not credible , with precision and recall in the range of 70 % to 80 % .
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