Improving rumor detection by promoting information campaigns with transformer-based generative adversarial learning

• Main Authors: MA, Jing, LI, Jun, GAO, Wei, YANG, Yang, WONG, Kam-Fai
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2023
• Subjects: Blogs; Feature extraction; Generative Adversarial Networks; Generators; Information Campaigns; Recurrent neural networks; Rumor Detection; Self-attention; Social networking (online); Training; Transformer; Transformers; Databases and Information Systems; Numerical Analysis and Scientific Computing
• Online Access: https://ink.library.smu.edu.sg/sis_research/6659; https://ink.library.smu.edu.sg/context/sis_research/article/7662/viewcontent/TKDE_RumorGAN.pdf
• Institution: Singapore Management University

Rumors can cause devastating consequences to individuals and our society. Analysis shows that the widespread of rumors typically results from deliberate promotion of information aiming to shape the collective public opinions on the concerned event. In this paper, we combat such chaotic phenomenon wi...