WSDMS: Debunk fake news via weakly supervised detection of misinforming sentences with contextualized social wisdom

• Main Authors: YANG, Ruichao, GAO, Wei, MA, Jing, LIN, Hongzhan, YANG, Zhiwei
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2023
• Subjects: fake news debunking; truthfulness; misinformation; sentence-level detection; research; Multiple Instance Learning (MIL); Weakly Supervised Detection of Misinforming Sentences (WSDMS); bag-level labels; article-level veracity; social media conversations; benchmarks; state-of-the-art baselines; debunking; sentence and article levels; Computer Sciences
• Online Access: https://ink.library.smu.edu.sg/sis_research/8454; https://ink.library.smu.edu.sg/context/sis_research/article/9457/viewcontent/2023.emnlp_main.94.pdf
• Institution: Singapore Management University

In recent years, we witness the explosion of false and unconfirmed information (i.e., rumors) that went viral on social media and shocked the public. Rumors can trigger versatile, mostly controversial stance expressions among social media users. Rumor verification and stance detection are different...