Proceedings ArticleDOI
Information credibility on twitter
Carlos Castillo,Marcelo Mendoza,Barbara Poblete +2 more
- pp 675-684
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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
Citations
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The spread of true and false news online
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Fake News Detection on Social Media: A Data Mining Perspective
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Fake News Detection on Social Media: A Data Mining Perspective
TL;DR: This survey presents a comprehensive review of detecting fake news on social media, including fake news characterizations on psychology and social theories, existing algorithms from a data mining perspective, evaluation metrics and representative datasets, and future research directions for fake news detection on socialMedia.
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Systematic Literature Review on the Spread of Health-related Misinformation on Social Media
TL;DR: An increasing trend in published articles on health-related misinformation and the role of social media in its propagation is observed, and the most extensively studied topics involving misinformation relate to vaccination, Ebola and Zika Virus, although others, such as nutrition, cancer, fluoridation of water and smoking also featured.
References
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Proceedings ArticleDOI
Detecting and Tracking the Spread of Astroturf Memes in Microblog Streams
Jacob Ratkiewicz,Michael Conover,Mark R. Meiss,Bruno Gonçalves,Snehal Patil,Alessandro Flammini,Filippo Menczer +6 more
TL;DR: In this article, the authors introduce an extensible framework that will enable the real-time analysis of meme diffusion in social media by mining, visualizing, mapping, classifying, and modeling massive streams of public microblogging events.
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TL;DR: The author of Six Degrees: The Science of a Connected Age is a founding partner of the Huffington Post, BuzzFeed, and ContagiousMedia.org.