Online deception and misinformation have been fueled by the deep penetration of the Internet and social media in support of personal and business communications. The identification of indicators and signals of deception or misinformation is instrumental to the detection task. We have investigated multiple dimensions of indicators of online deception, including lexical, structural, and discourse behaviors, in a variety of settings. In addition, we have developed and enhanced a variety of traditional machine learning and deep learning models for automatic deception detection and for augmentation of human detection.
Selected Publications
Zhang, D., G. Shan, M. Lee, L. Zhou, Z. Fu (2025), MT-GPD: A Multimodal Deep Transfer Learning Model Enhanced by Auxiliary Mechanisms for Cross-Domain Online Fake News Detection, Production and Operations Management, 34(8), 2448-2470.