I am an assistant professor in applied consumer analytics and strategic communication in the Department of Financial Planning, Housing and Consumer Economics at the University of Georgia. I received my Ph.D. from the Annenberg School for Communication, University of Pennsylvania.

My scholarship is at the intersection of computational social science, visual media, and science communication. My research applies cutting-edge computer vision methods to investigate the production and effects of visual messages across different communication contexts. Some examples include visual portrayals of politicians, images of climate change, COVID-19 visualizations, and fitspiration images on Instagram. My recent research, funded by the National Science Foundation, examines how attributes of misinformation claims in visual formats (e.g., photographs, videos, memes, and infographics) influence viewers’ credibility perceptions.

I also study science communication, with a focus on public perceptions of artificial intelligence technologies, such as facial recognition and self-driving cars. I am particularly interested in how emerging AI technologies are connected to debates about inequality and social justice and how these factors affect public opinions. In the wake of the pandemic, I develop a line of research on the polarization of science, which demonstrates the importance of ideologies in shaping our responses to issues such as COVID-19, vaccination, and AI applications.

My works have been published (or are forthcoming) in leading venues in multiple social science disciplines, including the Journal of Communication, Communication Research, New Media & Society, the International Journal of Press/Politics, Sociological Methods & ResearchPublic Understanding of Science, Risk Analysis, and the Proceedings of ACM Conference on Human Factors in Computing Systems. I have received multiple top paper awards from the International Communication Association and the National Communication Association.

I received my M.A. degree from the University of Wisconsin–Madison and B.S. degree from Peking University. I enjoy photography, hiking, camping, biking, museums, movies, open-world video games, and science writing for the general public.

Recent updates

April 2022

  • Our study “Fitspiration on Instagram: Identifying topic clusters in user comments to posts with objectification features” in Health Communication (coauthored with Volha Murashka and Jiaying Liu) is featured by ABC WBAY. Super fun project to look at how fitspiration accounts on Instagram use self-objectification and how these strategies affect audience comments.
  • My paper “Politics of COVID-19 vaccine mandates: Left/right-wing authoritarianism, social dominance orientation, and libertarianism” is online at Personality and Individual Differences.
  • Our paper “Image Clustering: An Unsupervised Approach to Categorize Visual Data in Social Science Research” (coauthored with Han Zhang) is online! Check this tweet summary.

March 2022

  • Our grant “Understanding how visual features of misinformation influence credibility perceptions” (with Cindy Shen) is awarded by the National Science Foundation!
  • Our paper on the morality of COVID-19 messages on Facebook (coauthored with Brin Xu) is accepted for presentation at ACCI 2022.
  • My article on how ideological components predict COVID-19 perceptions is now published in Risk Analysis. You can also read a news release on the article or my tweet summary.

February 2022

  • On Feb 11, I will give a talk about “emerging directions of computer vision applications in social science research” for the Agricultural Data Science program at the University of Georgia.

January 2022

  • Five papers accepted at ICA 2022!

2021

  • Our paper “Image Clustering: An Unsupervised Approach to Categorize Visual Data in Social Science Research” (coauthored with Han Zhang) is now forthcoming at Sociological Methods & Research. Check our preprint!
  • Excited that I received a top paper award from the National Communication Association.
  • My paper “Athec: A Python Library for Computational Aesthetic Analysis of Visual Media in Social Science Research” is now forthcoming in the Special issue “Images as Data” at Computational Communication Research. You can read the preprint or experiment with the codes.