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Using AI as a Tool for Social Analysis: Prospects and Challenges
Tue, August 11, 8:00 to 9:30am, TBASession Submission Type: Paper Session (90 minute)
Description
This session welcomes papers exploring the use of Artificial Intelligence (AI) as a tool for formal sociological analysis. Papers may include work using recently developed AI tools (e.g., large language models) to enhance or supplement existing sociological methodologies. Papers may also focus on developing strategies that use AI to innovate beyond existing sociological methods, generate new techniques and approaches for data coding, validation, and inference, or explore avenues for “in silico” experimentation and research. We also welcome papers outlining key methodological challenges, limitations, and pitfalls of using AI for sociological research.
Sub Unit
Presider
Individual Presentations
A Sociological Turing Test: Social Identity Cues Shape Who is Classified as Human Online - Benjamin Rochford, Duke University; Cathy Lee, Duke University; Michelle Qiu, University of Michigan; Alexander Volfovsky, Duke University; D. Sunshine Hillygus, Duke University; Christopher A. Bail, Duke University
Human versus LLM: Evaluating Effectiveness of Generative AI in Thematic Coding in the Interpretive Social Sciences - Neha Gondal, Boston University; Noor Toraif, University of Pennsylvania; John Balch, Cenetr for Mind and Culture
Large Language Models and Social Movement Framing: A Hybrid Inductive-Deductive Approach to Cross-National Media Analysis - Hanning Wang, University of Pittsburgh
Poisoning the Discourse: Detecting Implicit Poverty Stigma in U.S. Political Speech Through Masked Language Models - Yunseok Jeong, Korea University
Using large language models as a source of human behavioral data in social science experiments - Austin van Loon, Massachusetts Institute of Technology; Klint Kanopka, NYU Steinhardt