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FakeNews Detection Using Pre-trained Language Models and Graph Convolutional Networks
2020
MediaEval Benchmarking Initiative for Multimedia Evaluation
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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
dblp:conf/mediaeval/TuanM20
fatcat:o7hl2zds55brlo5ngjfvyujtyi