Predicting viral rumors and vulnerable users with graph-based neural multi-task learning for infodemic surveillance

• Main Authors: ZHANG, Xuan, GAO, Wei
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: Infodemic surveillance; Neural multi-task learning; Rumor detection; User vulnerability; Virality prediction; Databases and Information Systems; Graphics and Human Computer Interfaces; Information Security
• Online Access: https://ink.library.smu.edu.sg/sis_research/8320; https://ink.library.smu.edu.sg/context/sis_research/article/9323/viewcontent/PredictingViralRumors_av.pdf
• Institution: Singapore Management University

In the age of the infodemic, it is crucial to have tools for effectively monitoring the spread of rampant rumors that can quickly go viral, as well as identifying vulnerable users who may be more susceptible to spreading such misinformation. This proactive approach allows for timely preventive measu...