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Integrating Generative Artificial Intelligence into Social Science Research: Measurement, Prompting, and Simulation

DSEID
DSEID-001-4967452
DOI
10.1177/00491241251339184
Journal
Sociological Methods & Research
Publisher
SAGE Publications
Published
2025-8
Status
metadata_only

Abstract

Generative artificial intelligence (AI) offers new capabilities for analyzing data, creating synthetic media, and simulating realistic social interactions. This essay introduces a special issue that examines how these and other affordances of generative AI can advance social science research. We discuss three core themes that appear across the contributed articles: rigorous measurement and validation of AI-generated outputs, optimizing model performance and reproducibility via prompting, and novel uses of AI for the simulation of attitudes and behaviors. We highlight how generative AI enable new methodological innovations that complement and augment existing approaches. This essay and the special issue’s ten articles collectively provide a detailed roadmap for integrating generative AI into social science research in theoretically informed and methodologically rigorous ways. We conclude by reflecting on the implications of the ongoing advances in AI.

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Metadata

Title
Integrating Generative Artificial Intelligence into Social Science Research: Measurement, Prompting, and Simulation
Delta ID
DSEID-001-4967452
Authors
Thomas Davidson, Daniel Karell
Abstract source
crossref
Source URL
None
Access
closed_or_uncertain
Licence
unknown
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Record history

WhenEventFieldOldNew
2026-06-18 19:37:53.011249+00:00identifier_assignedDSEIDDSEID-001-4967452