Workshop Proceedings of the 17th International AAAI Conference on Web and Social Media

Workshop: Mediate 2023: News Media and Computational Journalism Workshop

DOI: 10.36190/2023.24

Published: 2023-06-01
Combating the COVID-19 Infodemic: Untrustworthy Tweet Classification using Heterogeneous Graph Transformer
Lin Ai, Zizhou Liu, Julia Hirschberg

While COVID-19 has affected most of the world, attempts to control it have been difficult due to the lack of trustworthy information about the virus's origin, severity, effective treatments, and prevention measures. To address this, we have collected RTCas-COVID-19, a large corpus of 35M COVID-19 tweets from 2020, and weak-labeled 2M with a semi-supervised approach. We have also developed an inductive framework, RTCS-HGT (Retweet Cascade Subgraph Sampling Heterogeneous Graph Transformer), which achieves 0.918 test accuracy on tweet trustworthiness classification on our dataset and improves training time by 93%.