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NORC at the University Chicago

Hy Tran

Pronouns: He/Him

Senior Data Scientist
Public Health
Social Data Collaboratory
Hy employs advanced data science techniques to analyze and interpret social media data.

Hy is a senior data scientist at the Social Data Collaboratory at NORC, with over a decade of experience in public health research. Hy's expertise lies in harnessing social media data, employing advanced machine learning techniques, and leveraging natural language processing to derive insights from unstructured data. With a deep understanding of data from various sources, including social media, legacy media, national surveys, marketing, and product sales, Hy focuses on innovative social media research methodologies. This includes the collection and management of unstructured data and the application of AI and machine learning to analyze these data comprehensively.

Hy has played a pivotal role in NIH, NCI, and CDC funded projects, utilizing cutting-edge machine learning algorithms to dissect and understand tobacco product messaging across major social platforms like Twitter/X, Instagram, and Facebook.

Before joining NORC, Hy was a research specialist at the Institute for Health Research and Policy (IHRP), where he developed and deployed innovative methodologies for the acquisition and analysis of tobacco product information in public media.

Project Contributions

Menthol Cigarettes & Social Justice Views

Understanding the perceptions of those targeted by marketing of flavored tobacco

Client:

Robert Wood Johnson Foundation

America in One Room

A “deliberative polling” experiment to bridge American partisanship

Client:

Stanford University

Developing a Supervised Model of Online COVID Vaccine Information

Examining AI biases in model development to accurately detect and classify online COVID-19 vaccine information

Client:

Amazon Web Services (AWS)

Social Media’s Influence on Flavored Tobacco Use

Investigation of youth-targeted flavored tobacco promotion on social media to inform regulatory decisions

Client:

National Institute on Drug Abuse; Food & Drug Administration

How Right Now / Qué Hacer Ahora

A communication initiative to increase people’s resilience during the COVID-19 pandemic

Client:

Centers for Disease Control and Prevention and the National Foundation of the Centers for Disease Control and Prevention

Using Innovative Machine Learning to Detect Support and Opposition to E-Cigarette Use Prevention Messaging on Twitter and TikTok

First study to examine the content, sources, and patterns of diffusion of E-cigarette prevention campaigns

Client:

National Cancer Institute

Publications

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