Congratulations to CHATR Lab PhD candidate Emily McKinley, who received the Best Speaker Award for her parallel talk, "Human?: Validating Large Language Models as Proxies for Human Participants in Persuasive Communication Research," at the 2026 International Conference on the Science of Science and Innovation (ICSSI 2026).

Abstract: The prevalence of short video platforms, combined with the ineffectiveness of age verification mechanisms, raises concerns about the potential harm facing children and teenagers in an algorithm-moderated online environment. We conducted multimodal feature analysis and thematic topic modeling of 4,492 short videos recommended to children and teenagers on Instagram Reels, TikTok, and YouTube Shorts, collected as a part of an algorithm auditing experiment.

Abstract: The contemporary media landscape is characterized by sensational short videos. While prior research examines individual multimodal features’ effects, the collective impact of multimodal features on viewer engagement with short videos remains unknown. Grounded in the theoretical framework of Message Sensation Value (MSV), this study develops and tests a computational model of MSV with multimodal feature analysis and human evaluation of 1,200 short videos.

Dr. CJ Calabrese, an alumnus of the doctoral program in the Department of Communication at UC Davis, has received the Early Career Award from the Public Health Education and Health Promotion section of the American Public Health Association. The award recognizes scholars who make an outstanding contribution to public health through their research and leadership in the first ten years after receiving their doctorate. 

The CHATR Lab is proud to announce that PhD candidate Emily McKinley and coauthors have been awarded a Best Research Award at the Computational Social Science Escape 2025 conference for their innovative work on using large language models (LLMs) to synthesize human responses in persuasive contexts.

We are proud to announce that Dr. Jingwen Zhang was the inaugural recipient of the Annual Lingnan Award for Excellence in Health Informatics. This distinguished honor was presented by CITRIS Health, a division of CITRIS and the Banatao Institute at the University of California, in partnership with the First Affiliated Hospital at Sun Yat-sen University, China. Dr.

Abstract: 
Objective
This study presents a pilot randomized controlled trial to assess the usability, feasibility, and initial efficacy of a mobile app-based relational artificial intelligence (AI) chatbot (Exerbot) intervention for increasing physical activity behavior.

Abstract: The perception of reality could matter more than reality itself when it comes to disease outbreaks. News media are important sources of information during global disease outbreaks, such as the COVID-19 pandemic. Drawing on theories of fear appeals and the social ecological model, we conducted multilevel modeling analyses to examine how media-level and community-level factors influenced the public’s risk perceptions of COVID-19 and frequencies of preventive behaviors in the United States, United Kingdom, Canada, Australia, and India.

Abstract: Emotionality is a well-established strategy for boosting audience engagement on social media. While fact-checking is positioned to provide objective information, fact-checking posts on social media often involve heightened emotionality. How much emotionality is present and how emotionality influences audience engagement and public sentiment toward fact-checked targets remain largely understudied.

Are you eager to contribute to groundbreaking research with the CHATR Lab? We welcome applicants from all backgrounds—whether you're an advanced computer programmer, statistician, communication scholar, or just beginning your research journey, we have opportunities for you to grow and learn. This is a fantastic chance to engage in cross-disciplinary research and enhance your resume.

Abstract: Fact-checking labels have been widely accepted as an effective misinformation correction method. However, there is limited theoretical understanding of fact-checking labels’ impact. This study theorizes that language intensity influences fact-checking label processing and tests this idea through a multi-method design. We first rely on a large-scale observational dataset of fact-checking labels from 7 U.S.

Congratulations to Emily McKinley on passing her Qualifying Exam and becoming a PhD candidate on May 14th.

Haoning Xue will join the Department of Communication at the University of Utah as an assistant professor in Emerging Media and Innovation in Fall 2024. Haoning uses experimental and computational methods to study digital information integrity and health communication.

Dr. Jingwen Zhang and Ph.D. candidate Haoning Xue received the National Science Foundation (NSF) Doctoral Dissertation Research Improvement Grants in Decision, Risk and Management Sciences to support Haoning's dissertation titled "Communicating risks in a sensational media environment - Using short video multimodal features to attract attention and reduce psychological reactance for persuasion."

Below is the project abstract: