Nga Than
Senior Data Scientist, Prudential Financial
Associated Researcher, Stone Center - CUNY - The Graduate Center

Nga Than is a Senior Data Scientist at Prudential Financial. She earned a Ph.D. in Sociology from City University of New York – The Graduate Center. Her data science and scholarly research interests are in Artificial Intelligence, Generative AI, Machine Learning, Human-computer Interaction, and how AI introduces new ways to conceptualize social problems. Her writings on AI & Society appear frequently at Montreal AI Ethics Institute, e27, The Gradient, VNExpress. As a mixed methods scholar, she has used a combination of computational methodologies and qualitative methodologies including as well as natural language processing to analyze large corpora of text data, interviewing, and participant observation. Her research has received support from the Andrew W. Mellon Foundation, German Academic Exchange Service (DAAD), Taiwan's Huayu Enrichment Scholarship, CUNY - Pre-dissertation Fellowship, CUNY - Doctoral Student Research Grant, and CUNY - Provost's Digital Innovation Grant.



  • Social Problem of Creativity in the Era of Generative Artificial Intelligence: This research explores how to conceptualize and reconceptualize the problem of creativity in the age of artificial intelligence and generative Artificial Intelligence. Using Boden's three conceptions of creativity: combinational, exploratory, and transformational, the project engages in how computational creativity scholars describe, and conceptualize different AI tools.

  • Generative AI as Sociological Methodology: This research uses Generative AI as a way to understand discourses of income inequality in the United States since the 1990s. The aim is to explore public discourses around income inequality through the newly available tools such as GPT-4 API, and ChatGPT.

  • Participatory Survey Research: This project utilizes participatory survey methodology powered by Machine Learning automated anlaysis to understand how the different publics (broadly defined) engage with the idea of public humanities, and public higher education.

Selected Publications

  • 2023. Color‐blind and racially suppressive discourses on German‐speaking Twitter: A mixed method analysis of the Hanau White nationalist shootings (with Friederike Windel, Krystal M. Perkins, and Maria Y. Rodriguez) [Link]

  • 2023. Attitudes about refugees and immigrants arriving in the United States: a conjoint experiment (with Liza G. Steele, Lamis Abdelaaty) [Link]

  • 2022. Training a Model=/≠ Generating Culture: The Meaning of Culture and the Prospect of Artificial Intelligibility (with Michael W. Raphael) [Link]

  • 2022. #Lorrydeaths: structural topic modeling of Twitter users' attitudes about the deaths of 39 Vietnamese migrants to the United Kingdom (with Friederike Windel, Liza G. Steele) [Link]

  • 2022. The Privacy Conundrum: An empirical examination of barriers to privacy among Indian social media users (with Abhishek Gupta, Ameen Jauhar) [Link]

  • 2022. Have you tried Neural Topic Models? Comparative analysis of neural and non-neural topic models with application to COVID-19 Twitter data (with Andrew Bennett, Dipendra Misra) [Link]

  • 2021. A Practical Guide for Teaching the Sociological Imagination (with Karen Okigbo, Sebastian Villamar-Santamaria, Anna Zhelnina, and Isabel Gil-Everaert). CUNY Scholarship on Manifold. The Teaching and Learning Center. [Link]

  • 2021. Between Two Crises: Artisanal Food Startup Founders in New York. Metropolitics [Link]

  • 2021. "Welcome to Gab" (with Maria Rodriguez, Friederike Windel, and Diane Yoong). Interdisciplinary Digital Engagement in Arts & Humanities (IDEAH) [Link]

  • 2020. "Community and the Digital Classroom." Blog. The Center for The Humanities. CUNY - The Graduate Center. [Link]

  • 2020. "Visualizing the Urban." The Journal of Interactive Technology and Pedagogy. [Link]