Towards low-resource rumor detection: Unified contrastive transfer with propagation structure

• Main Authors: LIN, Hongzhan, MA, Jing, YANG, Ruichao, YANG, Zhiwei, CHENG, Mingfei
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: Contrastive learning; Few-shot transfer; Low resource; Propagation structure; Rumor detection; Theory and Algorithms
• Online Access: https://ink.library.smu.edu.sg/sis_research/8731; https://ink.library.smu.edu.sg/context/sis_research/article/9734/viewcontent/Low_resourceRumourDetection_av.pdf
• Institution: Singapore Management University

The truth is significantly hampered by massive rumors that spread along with breaking news or popular topics. Since there is sufficient corpus gathered from the same domain for model training, existing rumor detection algorithms show promising performance on yesterday's news. However, due to a...