Challenges in Pre-Training Graph Neural Networks for Context-Based Fake News Detection: An Evaluation of Current Strategies and Resource Limitations

arXiv:2402.18179v1 Announce Type: new
Abstract: Pre-training of neural networks has recently revolutionized the field of Natural Language Processing (NLP) and has before demonstrated its effectiveness in computer vision. At the same time, advances around the detection of fake news were mainly driven by the context-based paradigm, where different types of signals (e.g. from social media) form graph-like structures that hold contextual information apart from the news article to classify. We propose to merge these two developments by applying pre-training of …

abstract advances arxiv challenges computer computer vision context cs.cl current detection evaluation fake fake news graph graph neural networks language language processing limitations natural natural language natural language processing networks neural networks nlp pre-training processing strategies training type vision