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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Posted Content
Fake news propagate differently from real news even at early stages of spreading
Zilong Zhao,Jichang Zhao,Yukie Sano,Orr Levy,Hideki Takayasu,Misako Takayasu,Daqing Li,Junjie Wu,Shlomo Havlin +8 more
TL;DR: In this article, the authors track large databases of fake news and real news in both, Weibo in China and Twitter in Japan from different culture, which include their complete traces of re-postings.
Journal ArticleDOI
AMFB: Attention based multimodal Factorized Bilinear Pooling for multimodal Fake News Detection
Rina Kumari,Asif Ekbal +1 more
TL;DR: It is empirically show that text, when combined with the image, can improve the performance of the model, and the complexity of the proposed model is significantly lower than the state-of-the-art models.
Twitter as a navigator for stranded commuters during the great east Japan earthquake.
TL;DR: The possibilities and problems of Twitter use under a rapidly changing disaster situation are described and if Twitter was an effective navigator for helping stranded commuters return home or find shelter is explored.
Journal ArticleDOI
Automated Credibility Assessment on Twitter
TL;DR: Practical implementation of TwitterBOT, a tool which is able to score submitted tweets while working in the native Twitter interface, and the process behind the design of an automated classi- fier for information credibility assessment are described.
Journal ArticleDOI
Deep spatial–temporal structure learning for rumor detection on Twitter
TL;DR: A spatial–temporal structure neural network for rumor detection, termed as STS-NN, which treats the spatial structure and the temporal structure as a whole to model the message propagation, and shows that the approach obtains better performance than baselines in both rumor classification and early 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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