May 20, 2025

In our Affiliate Highlights series, we share short interviews with members of our community, offering a glimpse into their research, interests, and what inspires their work.  This year, we are randomly selecting assistant and associate professors from our Affiliates program. 

Each feature includes a few brief questions (nothing too serious!) to help spark connections, highlight new opportunities, and maybe even introduce you to your next collaborator. This month, get to know JungHwan Yang and Rachel Hoopsick!

JungHwan Yang | assistant professor, communication

What are your main research interests?

My research explores how people access, engage with, and respond to political information in today’s fragmented media environment. I am particularly interested in the life cycle of real-world events—how they become news, which ones are selectively covered or ignored, and how people consume those stories. Understanding this process reveals media bias and shapes the public’s understanding of politics.

To investigate this, I am currently working on a case study of mass shootings, supported by the Cline Center for Advanced Social Research. Although hundreds of mass shootings occur each year, only a small number receive national media attention. Even when they do, different outlets frame these events with varying emphases and biases, and audiences interpret them through their own filters. This process plays a critical role in how individuals make sense of the world and form opinions about potential policy solutions. This project aims to uncover biases in both news production and audience consumption.

Another project, funded by the NSF, examines the political influence of social polls—informal, often viral polls shared on social media. Working as part of an interdisciplinary team of social scientists and computer scientists, we study whether these polls reflect genuine public opinion or create misleading signals that distort perceptions of political reality. Both projects contribute to my broader goal: understanding how information flows—or fails to flow—and how that shapes democratic life.

What are you most excited about in your research this year?

I am especially excited about how generative AI is opening up new possibilities for social science research. Thanks to large language models (LLMs) and other AI tools, we are now able to move beyond traditional content analysis to study more complex narrative structures in text, image, and video. Instead of simply identifying topics, we can examine how stories are framed, how people are portrayed, and what moral or emotional cues are embedded in the coverage.

In one of my ongoing projects, we are using generative AI in combination with human coders to analyze political TikTok videos during presidential campaigns. This work is especially timely, given that a growing number of young people now rely on TikTok as a primary source of political information. If this is where political learning is happening, we need to ask: what exactly are they learning? Generative AI enables us to answer this question at scale. I see this as a transformative moment for the field, and I am excited to help develop standards for using these tools responsibly and rigorously in social science.

Rachel Hoopsick | assistant professor, health and kinesiology

What are your main research interests? 

My research focuses on substance use and mental health in populations with high-stress occupations and life circumstances. I have expertise in behavioral and psychiatric epidemiology and use quantitative methods to examine how factors at individual, interpersonal, and societal levels influence behavioral health. I also study national trends in substance use, overdose, and suicidality by leveraging public health surveillance data. My goal is to inform prevention, policy, and practice to support underserved communities.

What drives your interest in this area of research?

I grew up in a low-income community where substance use and mental health struggles were part of everyday life. I’ve lost people I care about to overdose and suicide, and those losses stay with me. As a first-gen student, I was driven to understand why some communities carry such a heavy burden and how social and structural factors shape health. These personal experiences continue to guide my research and fuel my commitment to working with people who have lived/living experience to create more just, compassionate, and effective public health solutions. I think what’s most meaningful about public health is that each data point – every number – represents a real person, a family, a community. The insights we derive and the solutions we create can have tangible impacts locally, nationally, and globally. This motivates me every day.