Rumor detection on social media using hierarchically aggregated feature via graph neural networks

HIGHLIGHTS

  • who: Shouzhi Xu from the (UNIVERSITY) have published the Article: Rumor detection on social media using hierarchically aggregated feature via graph neural networks, in the Journal: (JOURNAL)
  • what: The authors propose a novel model for rumor detection based on Graph Neural Networks (GNN) named Hierarchically Aggregated Graph Neural Networks (HAGNN). The authors design the pooling module to aggregate node vectors and get the final representation vector of the entire graph. The authors propose the text-level feature generation module. The authors compare the proposed model with the following typical methods, including:.
  • how: This . . .

     

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