Proceedings ArticleDOI
Information credibility on twitter
Carlos Castillo,Marcelo Mendoza,Barbara Poblete +2 more
- pp 675-684
TLDR
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%.Abstract:
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%.read more
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Arabic corpora for credibility analysis
Ayman Al Zaatari,Rim El Ballouli,Shady Elbassuoni,Wassim El-Hajj,Hazem Hajj,Khaled Bashir Shaban,Nizar Habash,Emad Yehya +7 more
TL;DR: This paper focuses on building a public Arabic corpus of blogs and microblogs that can be used for credibility classification in Arabic and discusses the data acquisition approach and annotation process, provides rigid analysis on the annotated data and reports some results on the effectiveness of the data for credibility Classification.
References
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