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
Citations
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Technology adoption news and corporate reputation: sentiment analysis about the introduction of Bitcoin
TL;DR: In this paper, a panel vector autoregression model was used to incorporate series of data relating to news items, volume and sentiment, showing that the news about the adoption of a new technology has a positive impact on both the volume of tech-related tweets and the sentiment expressed in the tweets themselves, although the patterns of these two effects are different.
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Measuring information credibility in social media using combination of user profile and message content dimensions
TL;DR: With the proposed new features, the credibility of information provided in social media is increasing significantly indicated by better accuracy compared to the existing technique for all classifiers.
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Classification of Arabic Tweets: A Review
TL;DR: A comparison of previous surveys is presented, elaborating the need for a comprehensive study on Arabic Tweets, and machine learning algorithms and lexicon-based classifications are discussed comprehensively.
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Storyboarding for visual analytics
Rick Walker,Llyr ap Cenydd,Serban R. Pop,Helen C. Miles,Chris J. Hughes,William J. Teahan,Jonathan C. Roberts +6 more
TL;DR: Six principles of storyboarding for visual analytics are presented: composition, viewpoints, transition, annotability, interactivity and separability, which are used to develop epSpread, which is applied to VAST Challenge 2011 microblogging data set and to Twitter data from the 2012 Olympic Games.
Journal ArticleDOI
DTN: Deep triple network for topic specific fake news detection
TL;DR: A deep triple network (DTN) is proposed that leverages knowledge graphs to facilitate fake news detection with triple-enhanced explanations and results show that DTN outperforms conventionalfake news detection methods from different aspects, including the provision of factual evidence supporting the decision of fake news Detection.
References
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Proceedings ArticleDOI
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Proceedings ArticleDOI
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Proceedings ArticleDOI
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Proceedings ArticleDOI
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Proceedings ArticleDOI
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