About
My research centers on science, environmental, and crisis communication, visual communication, and computational social science. I am currently pursuing two related lines of inquiry. The first examines how we can design effective messages to foster public understanding, engagement, and acceptance of science and technology, from climate change to artificial intelligence. The second investigates how emerging forms of visual media, such as short videos, AI-generated visuals (deepfakes), and other visual content, are reshaping public engagement with science, risks, and disasters. I draw on both computational and experimental methods to address these questions.
I am proudly affiliated with the Media and Risk Lab at U-M, under the guidance of Prof. Hang Lu. I won top student paper awards from the International Communication Association in 2022 and the Society for Risk Analysis in 2025, respectively.
Selected publications:
Li, Y., & Lu, H. (In Press). Perceived legitimacy matters: Building public trust and acceptance of AI-generated news images through strategic AI disclosure. Journalism & Mass Communication Quarterly.
Li, Y., Zhang, A. L., & Lu, H. (2026). Stitching, dueting, and playing with science on TikTok: An AI-powered multimodal approach to understanding interactive science videos and audience engagement. Computational Communication Research, 8(4), 1-29.
Li, Y., Lu, H., & Yu, C. (2026). Navigating intersectional expectations: a computational multimodal analysis of the effects of identities and communication styles on public engagement with science on TikTok. Information, Communication & Society, 1-22.
Li, Y., Yu, B., & Dai, J. (2024). “Climate change” or “global warming”? The (Un) Politicization of climate in Chinese social media platform. Environmental Communication, 18(7), 927-944.
