Contrastive Domain Adaptation for Early Misinformation Detection: A Case Study on COVID-19. (arXiv:2208.09578v3 [cs.CV] UPDATED)

Despite recent progress in improving the performance of misinformation
detection systems, classifying misinformation in an unseen domain remains an
elusive challenge. To address this issue, a common approach is to introduce a
domain critic and encourage domain-invariant input features. However, early
misinformation often demonstrates both conditional and label shifts against
existing misinformation data (e.g., class imbalance in COVID-19 datasets),
rendering such methods less effective for detecting early misinformation. In
this paper, we propose contrastive adaptation network for early misinformation
detection …

arxiv case case study covid covid-19 detection domain adaptation misinformation study