Conference Proceeding

Fake News Identification on Twitter with Hybrid CNN and RNN Models

Citation

Ajao O, Bhowmik D & Zargari S (2018) Fake News Identification on Twitter with Hybrid CNN and RNN Models. In: SMSociety '18 Proceedings of the 9th International Conference on Social Media and Society. International Conference on Social Media and Society - SMSociety '18, 18.07.2018-20.07.2018. Copenhagen, Denmark: ACM Press, pp. 226-230. https://doi.org/10.1145/3217804.3217917

Abstract
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.

StatusPublished
FundersSheffield Hallam University
Publication date31/12/2018
PublisherACM Press
Place of publicationCopenhagen, Denmark
ISBN9781450363341
ConferenceInternational Conference on Social Media and Society - SMSociety '18
Dates

Research centres/groups