Research Projects

My research aims to deepen our understanding of the role of social contexts in the patterns of social intearctions and individual beliefs in the field of social networks, culture, and political polarization. I am also interested in causal inference and multilevel approaches to examine how complex social environments influence population health outcomes and health disparities. Below, I describe my ongoing research projects across three different fields: (i) networks and culture, (ii) health, and (iii) social cohesion and trust. Also, see Other section for other exciting projects that do not fall into these three categories.

Dynamics of Networks, Culture, and Polarization

Ego-centric networks

Examining the long-term changes in the characteristics of core discussion networks helps us understand how social relations have evolved in society. I have collected two unique network data sets to study how spatial and temporal contexts shape individuals’ beliefs and social relationships through politicization and selective activation. Currently, I am working on two project using this data to examine: (i) how people perceive others’ infection status in their social networks during the COVID-19 pandemics, and (ii) how neighborhood contexts and social networks jointly shape intergroup attitudes during the pandemic.

Grant Support
  • National Science Foundation.
  • American Assembly at Columbia University.

2023 “Transformation of social relationships in COVID-19 America: Remote communication may amplify political echo chambers.”, Science Advances 9(51):eadi1540 Paper, Code and data

2021 “Close Relationships in Close Elections”, Social Forces 100(1): 400-425. Paper, Code and data

2020 “Political Isolation in America”, Network Science 8(3): 333-355. Paper, Code and data

2017 “Important Matters in Politial Context”, Sociological Science 8(3): 333-355. Paper, Code and data

Deliberation on social media

In a democratic society, citizens often disagree but need to communicate with one another for the collective good. However, severe disagreement can lead to breaking social ties among those with opposing views. How can people sustain large social circles with diverse opinions that facilitate democratic discussion and deliberation in an era of increased polarization? To answer this and related questions, I have led a unique large-scale data collection of all posts, comments, and likes across popular political forums on Facebook from 2015 to early 2017 and a unique text annotation survey that considers the context of social media comments with Barum Park (Cornell University) and Daniel McFarland (Stanford University).

Please visit Networks in Context lab to get information about the current works that we are doing.

Grant Support
  • National Science Foundation.

LLM, culture, and opinion dynamics

I am interested in studying how people organize a diverse set of beliefs across different contexts while using their correlated responses to survey questions to measure individuals’ cultural belief systems. Recently, I demonstrate that large language models can be useful for studying public opinion dynamics in surveys. With Junsol Kim, I continue to explore how LLMs can be useful for studying the patterns of cultural belief systems across different periods across different countries.

Working Papers

Lee, Byungkyu. “The Contextual Activation in Belief Networks.” American Journal of Sociology, Revise and Resubmit.

Kim, Junsol and Byungkyu Lee. “AI-Augmented Surveys: Leveraging Large Language Models and Surveys for Opinion Prediction.” Under Review.

Social Contexts and Health

Another stream of my research examines how social environments and health policy determine individual-level and population-level health outcomes.

Mental health

My prior work, published before starting my PhD in the U.S., shows that social support lowers the likelihood of developing PTSD among female North Korean refugees and that positive relationships with parents and peers jointly improve Korean adolescents’ life satisfaction. I continue my research on mental health in the US contexts. In a paper published in the American Journal of Sociology, we propose a new methodological framework that differentiates the influence of highly depressed peers from that of non-depressed peers and present a theoretical framework that explains how the extent of self-selection affects the dynamics of peer influence on depression. This paper was awarded as the co-winner of the 2022 Best Publication Award on the Sociology of Mental Health from the American Sociological Association.

I am currenly using the ego-centric network data during the COVID-19 pandemic that I described above to study how social contexts and environments shape loneliness and isolation in America.

Lee, Dohoon, and Byungkyu Lee. 2020. “The Role of Multilayered Peer Groups in Adolescent Depression: A Distributional Approach.” American Journal of Sociology 125(6):1513–58.


Although existing literature has consistently documented significant effects of community and school contexts on suicidal thoughts and attempts, little is known about multilevel determinants of completed suicide due to the lack of an appropriate comparison group for those who die by suicide. My recent collaborative work, published in the Proceeding of National Academy of Science, overcomes this challenge by harmonizing 2005-2011 data from the National Violent Death Reporting System (NVDRS) and the American Community Survey (ACS) through geographic matching at the county levels. Using this data, we show that demographic homogeneity of communities is associated with a lower risk of suicide, especially for high-risk groups such as the divorced population. This paper received a 2020 Cozzarelli Prize Finalist award from the PNAS Editorial Office.

Bernice and I have been refining the methodology to integrate NVDRS data with other datasets, which enables us to investigate the perplexing trend of rising suicide rates amidst falling unemployment in the U.S. since the 2007 Great Recession and to estimate the population prevalence and risk of suicide for the gay and lesbian population in the US.

Grant Support
  • American Foundation for Suicide Prevention
Working Papers

Lee, Byungkyu and Bernice Pescosolido. “Misery Needs Company: Contextualizing the Link Between Unemployment and Suicide Under Labor Market Precarity.” American Sociological Review, Revise and Resubmit.

Pescosolido, Bernice A., Byungkyu Lee, and Karen Kafadar. 2020. “Cross-Level Sociodemographic Homogeneity Alters Individual Risk for Completed Suicide.” Proceedings of the National Academy of Sciences 117(42):26170–75.

Opioid epidemics

Recent trends in the U.S. opioid epidemic present a paradox: opioid overdose mortality has risen despite precipitous declines in opioid prescriptions since 2012. In a paper published in JAMA Network Open, we show that the “opioid paradox” arises from the success — not failure — of state interventions to control the supply of opioid prescriptions. This paper has changed the course of research on the U.S. opioid epidemic by highlighting that curtailing the supply of prescription opioids is not a panacea without addressing the fundamental causes of demand for opioids.

Currently, I am investigating the role of medicolegal death investigation systems and death investigators certified by the American Board of Medicolegal Death Investigators in uncovering hidden opioid deaths.

Lee, Byungkyu, Wanying Zhao, Kai-Cheng Yang, Yong-Yeol Ahn, and Brea L. Perry. “Systematic Evaluation of State Policy Interventions Targeting the US Opioid Epidemic, 2007-2018.” JAMA Network Open. 4(2): e2036687.

Lee, Byungkyu, Kai-Cheng Yang, Patrick Kaminski, Peng Siyun, Meltem Odabas, Gupta Sumedha, Hank Green, Yong-Yoel Ahn, and Brea Perry. “Substitution of Non- Pharmacologic Therapy with Opioid Prescribing for Pain During the COVID-19 Pan- demic.” JAMA Network Open. 4(12):e2138453.

Social Cohesion and Trust

I am interested in studying the relational foundation for social cohesion and trust using survey experiments and analysis of large-scale digital trace data.

Relational trust activation

Sociologists have demonstrated that trust is intimately embedded within social relationships we have with other persons or objects, but previous research has been unable to show the causal link between social ties and the formation of relational trust. In collaboration with Peter Bearman (Columbia University), we design a novel survey experiment to identify the causal effect of activating different dimensions of social ties (e.g., emotional, and instrumental ties) on relational trust.

We have completed data collection. As part of survey data collection, we also asked how people define trust when they say they trust other people. We are currently analyzing the survey experiment data as well as open-ended text questions together to advance our understanding of the emotional foundation of relational trust.

Grant Support
  • Meta

Social capital through everday meetups

Social capital is a crucial determinant of individual and community well-being, influencing employment, health, and crime outcomes. It benefits communities by enhancing social interactions, trust, and collective problem-solving. However, as social capital consists of social connections, trust, and community engagements, it is challenging to measure its multifaceted constructs, particularly across a wide range of cities. With Myeong Lee and Brian Levy (George Mason University), we integrate survey and digital trace data to comprehensively measure social capital through group-level associations in the U.S. cities by drawing on the complementary strengths of the Meetup data (low cost, geographic coverage, temporal precision, objective measures) and survey data (representative sample, benchmark, subjective measures).

We are currently in the process of developing a survey to conduct a preliminary case study focusing on neighborhoods in Chicago. Additionally, we are actively pursuing research grants to expand our data collection efforts.

Public sentiments toward AI technology

In an era where AI drives decisions in healthcare diagnoses, financial investments, and even personalized education pathways, it is crucial to understand the mechanisms and trends of public trust in this pervasive technology. As assessing people’s reactions to AI-related news helps us understand the depth and dimensions of their trust in AI, this project delves into how advancements in AI have influenced public attitudes towards AI using reactions to AI-related news articles as a lens. By analyzing the public reactions and comments to the AI-related news in the New York Times from 2010 to 2023, we aim to discern dominant themes in public discourse surrounding AI, understand shifts in institutional trust, and uncover the broader implications of AI’s role in shaping societal confidence in these systems.

Trust in AI in medical domains

With Gil Eyal (Columbia University) and Simone Zhang (NYU), we study the extent to which patients trust generative AI about real-life diagnoses compared to medical professionals. A recent study claimed that AI-generated medical advice on a subreddit surpassed that of human doctors, suggesting that gaining trust in AI could be straightforward. However, this study faced several methodological issues, making its findings unreliable. Our goal is to address these shortcomings and establish a research framework for studying trust in AI within medicine. We gather data from a medical website featuring verified interactions between doctors and patients, contrasting it with subreddit data. This approach will inform the design of a survey experiment aimed at understanding the factors influencing trust in AI in medical contexts.


PhD/faculty exchange networks in sociology

In a collaborative project with Koji Chavez, Eehyun Kim, and Anne Kavalerchik (Indiana University), we leverage data on faculty lists from over 100 PhD-granting institutions in sociology to explore the dynamics of faculty and PhD exchange networks. Preliminary findings indicate a reinforcement of existing hierarchies. In addition, we matched the data with the list of sociology graduate students and found the signs of substantial gender inequality. These research contributes to a deeper understanding of the systemic inequalities and structural dynamics that shape career trajectories in sociology and beyond.

Partisan gaps in COVID-19 vaccinations rates

I investigate partisan gaps in COVID-19 vaccinations with James Chu (Columbia University). Drawing on nationally representative and longitudinal survey data from April 2020 to March 2022, we show that non-voters, representing about a third of the U.S. population, had the lowest vaccination rate (57%) by March 2022, significantly lower than Republican voters (67%). Further, non-voters are less likely to trust physicians and experience more socio-economic hardships and social isolation than voters. These results underscore the importance of developing COVID-19 vaccination policies to target this overlooked and highly vulnerable one-third of the population.

The structure of terrorist networks

One of the long-standing puzzles in the literature on terrorism is how terrorists can organize their networks to prevent their core leadership group from being detected, while simultaneously maintaining the capacity for coordinated action under severe state repression. In a collaborative project, we aim to solve this puzzle, the trade-off between secrecy and efficiency by building an agent-based model. We identify a network structure that is robust to penetration and capable of sustained action and growth even under a strong repressive regime. An implication of this work is that observed data on terrorist networks are likely to be partial. We illustrate this point by comparing six major characteristics of networks detected by police in the simulation against two terrorist networks – the 9/11 terrorist network and the recent Islamic State terrorist network in Europe – observed in the real world.

Genetic influence on network positions

In a working paper in collaboration with Dalton Conley (Princeton University) and Ramina Sotoudeh (Yale University), we investigate the role of social networks in the process of social stratification, by identifying the genetic-versus-social origin for adolescents’ social positions in peer environments. Against several studies recently reporting sizable genetic influence on network position and peer characteristics, our reanalysis of the Add Health data shows that prior “statistically significant” heritability estimates for ten network outcomes are overestimated, which are driven by gene-environment confounding (manifested by strong mutual friendship ties among identical twins). This paper suggests that, if genes matter for complex network outcomes, they do so only through indirect pathways that are fundamentally social.