FakeNews Detection Using Pre-trained Language Models and Graph Convolutional Networks

Nguyen Manh Duc Tuan, Pham Quang Nhat Minh
2020 MediaEval Benchmarking Initiative for Multimedia Evaluation  
We introduce methods for detecting FakeNews related to coronavirus and 5G conspiracy based on textual data and graph data. For the Text-Based Fake News Detection subtask, we proposed a neural network that combines textual features encoded by a pre-trained BERT model and metadata of tweets encoded by a multi-layer perceptron model. In the Structure-Based Fake News Detection subtask, we applied Graph Convolutional Networks (GCN) and proposed some features at each node of GCN. Experimental results
more » ... show that textual data contains more useful information for detecting FakeNews than graph data, and using meta-data of tweets improved the result of the text-based model.
dblp:conf/mediaeval/TuanM20 fatcat:o7hl2zds55brlo5ngjfvyujtyi