Defending Democracy: Using Deep Learning to Identify and Prevent Misinformation
Abstract
The rise in online misinformation in recent years threatens democracies by distorting authentic public discourse and causing confusion, fear, and even, in extreme cases, violence. There is a need to understand the spread of false content through online networks for developing interventions that disrupt misinformation before it achieves virality. Using a Deep Bidirectional Transformer for Language Understanding (BERT) and propagation graphs, this study classifies and visualizes the spread of misinformation on a social media network using publicly available Twitter data. The results confirm prior research around user clusters and the virality of false content while improving the precision of deep learning models for misinformation detection. The study further demonstrates the suitability of BERT for providing a scalable model for false information detection, which can contribute to the development of more timely and accurate interventions to slow the spread of misinformation in online environments.
Cite
@article{arxiv.2106.02607,
title = {Defending Democracy: Using Deep Learning to Identify and Prevent Misinformation},
author = {Anusua Trivedi and Alyssa Suhm and Prathamesh Mahankal and Subhiksha Mukuntharaj and Meghana D. Parab and Malvika Mohan and Meredith Berger and Arathi Sethumadhavan and Ashish Jaiman and Rahul Dodhia},
journal= {arXiv preprint arXiv:2106.02607},
year = {2021}
}