The present invention belongs to the field of fake news detection, and specifically relates to a fake news detection method based on hierarchical
pooling of interaction graphs. The method comprises: constructing a comment graph and a propagation
graph based on user comment interaction information, wherein each
sentence of the news to be detected, the tweets of the news to be detected, and each comment of the tweets are used as nodes of the comment graph, and the text semantic features of each node are used as node attributes; the news to be detected, each original
tweeter of the news to be detected, and each forwarding user of each original
tweeter are used as nodes of the propagation graph, and the
social profile of each user is used as user node attributes; using a node selection-based
pooling method to perform hierarchical
pooling on the comment graph, with each pooling layer being used to retain key content nodes; using a
node clustering-based pooling method to perform hierarchical pooling on the propagation graph, with each pooling layer being used to capture the characteristics of the propagation group; and using the pooling results to evaluate the authenticity of the news to be detected. The present invention can effectively improve the speed and accuracy of fake news detection.