Contributed Papers
Topics in Text Analysis: Topic Modeling, LLMs, and Beyond
Section on Text Analysis co: Section on Text Analysis
About this session
This contributed session covers various topics in text analysis, including applications of generative AI, topic modeling, and more traditional text classification tasks. Application domains span federal surveys, precision medicine, national archives, and even the development of novel statistical methodology.
6 Presentations
Enhancing Research Discovery with LLMs: A Comparative Study of Traditional Topic Modeling Algorithms
10:35 AM - 10:50 AM
Co-authors: Amir Alipour Yengejeh (University of Central Florida), Amir Alipour Yengejeh (University of Central Florida), Larry Tang (University of Central Florida)
10:50 AM - 11:05 AM
Co-authors: Tomer Zur (The Harris Poll), Tomer Zur (The Harris Poll), Coleen Schofield (Harris Poll)
11:05 AM - 11:20 AM
11:20 AM - 11:35 AM
Co-authors: Emily Hadley (RTI International), Dale Holstein (RTI International), Michael Long (RTI International), Michael Long (RTI International), Andy Kawataba (RTI International), Ethan Ritchie (RTI International), John Bollenbacher (RTI International), Michael Wenger (RTI International), Stuart Allen (RTI International)
11:35 AM - 11:50 AM
Co-authors: Hanjia Gao (University of California, Irvine), Qing Nie (University of California, Irvine: Mathematics; Developmental and Cell Biology), Hanjia Gao (University of California, Irvine), Annie Qu (University of California At Irvine)
11:50 AM - 12:05 PM
Co-authors: Madeline Kelsch (University of Michigan), Madison Hall (University of Michigan), Madeline Kelsch (University of Michigan), Conor York (University of Michigan), Tianyu Hu (University of Michigan), Cameron Milne (Reveal Global Consulting), Taylor Wilson (Reveal Global Consulting, LLC)