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    Fake News identification on Twitter with Hybrid CNN and RNN Models

    Ajao, Oluwaseun ORCID logoORCID: https://orcid.org/0000-0002-6606-6569, Bhowmik, Deepayan and Zargari, Shahrzad (2018) Fake News identification on Twitter with Hybrid CNN and RNN Models. In: SMSociety '18: International Conference on Social Media and Society, 18 July 2018 - 20 July 2018, Copenhagen, Denmark.

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    The problem associated with the propagation of fake news continues to grow at an alarming scale. This trend has generated much interest from politics to academia and industry alike. We propose a framework that detects and classifies fake news messages from Twitter posts using hybrid of convolutional neural networks and long-short term recurrent neural network models. The proposed work using this deep learning approach achieves 82% accuracy. Our approach intuitively identifies relevant features associated with fake news stories without previous knowledge of the domain.

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