Stand for Something or Fall for Everything: Predict Misinformation Spread with Stance-Aware Graph Neural Networks

Zihan Chen, Jingyi Sun, Rong Liu, Feng Mai

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Although pervasive spread of misinformation on social media platforms has become a pressing challenge, existing platform interventions have shown limited success in curbing its dissemination. In this study, we propose a stance-aware graph neural network (stance-aware GNN) that leverages users’ stances to proactively predict misinformation spread. As different user stances can form unique echo chambers, we customize four information passing paths in stance-aware GNN, while the trainable attention weights provide explainability by highlighting each structure's importance. Evaluated on a real-world dataset, stance-aware GNN outperforms benchmarks by 32.65% and exceeds advanced GNNs without user stance by over 4.69%. Furthermore, the attention weights indicate that users’ opposition stances have a higher impact on their neighbors’ behaviors than supportive ones, which function as social correction to halt misinformation propagation. Overall, our study provides an effective predictive model for platforms to combat misinformation, and highlights the impact of user stances in the misinformation propagation.

Original languageEnglish
Title of host publicationInternational Conference on Information Systems, ICIS 2023
Subtitle of host publication"Rising like a Phoenix: Emerging from the Pandemic and Reshaping Human Endeavors with Digital Technologies"
ISBN (Electronic)9781713893622
StatePublished - 2023
Event44th International Conference on Information Systems: Rising like a Phoenix: Emerging from the Pandemic and Reshaping Human Endeavors with Digital Technologies, ICIS 2023 - Hyderibad, India
Duration: 10 Dec 202313 Dec 2023

Publication series

NameInternational Conference on Information Systems, ICIS 2023: "Rising like a Phoenix: Emerging from the Pandemic and Reshaping Human Endeavors with Digital Technologies"

Conference

Conference44th International Conference on Information Systems: Rising like a Phoenix: Emerging from the Pandemic and Reshaping Human Endeavors with Digital Technologies, ICIS 2023
Country/TerritoryIndia
CityHyderibad
Period10/12/2313/12/23

Keywords

  • Echo Chamber
  • Graph Neural Networks
  • Misinformation Spread
  • User Stance

Fingerprint

Dive into the research topics of 'Stand for Something or Fall for Everything: Predict Misinformation Spread with Stance-Aware Graph Neural Networks'. Together they form a unique fingerprint.

Cite this