Rumor Detection with a novel graph neural network approach

Understand

The wide spread of rumors on social media has caused a negative impact on people's daily life, leading to potential panic, fear, and mental health problems for the public.

• How to debunk rumors as early as possible remains a challenging problem.
• Existing studies mainly leverage information propagation structure to detect rumors, while very few works focus on correlation among users that they may coordinate to spread rumors in order to gain large popularity.
• In this paper, we propose a new detection model, that jointly learns both the representations of user correlation and information propagation to detect rumors on social media.