Fake news is one of the biggest challenging issues in today's technological world and has a
huge impact on the population's decision-making and way of thinking. Disinformation can be …

Abstract In recent years, Graph Neural Networks (GNNs) have become a key technique to
address various graph-based machine learning tasks. Most of existing GNNs use simple …

Nowadays, social media has become the key source of information for anyone seeking
about current events across the world. This information may be fake or real news. On social …

Multimodal fake news detection often involves modelling heterogeneous data sources, such
as vision and language. Existing detection methods typically rely on fusion effectiveness and …

Multimodal fake news detection often involves modelling heterogeneous data sources, such
as vision and language. Existing detection methods typically rely on fusion effectiveness and …

A promising tool for addressing fake news detection is Graph Neural Networks (GNNs).
However, most existing GNN-based methods rely on binary classification, categorizing news …

We have attempted to capture a sense of the scientific state of the art in studying social
media platforms, including data collection from platforms, understanding platform behavior …

Distinguishing truth from deception requires innovative tools in an era of misinformation.
Misinformation, such as fake news and rumors, poses a serious threat to information …