Browse 4 peer-reviewed papers from University Of Minnesota spanning Sociological Methods, Generative AI (2024–2025). Research powered by Prolific's high-quality participant data.
This page lists 4 peer-reviewed papers from researchers at University Of Minnesota in the Prolific Citations Library, a curated collection of research powered by high-quality human data from Prolific.
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Authors: S Zhang, J Xu, AJ Alvero
Year: 2025
Published in: Sociological Methods & Research, 2025 - journals.sagepub.com
Institution: University of Maryland, Indiana University, University of Minnesota Duluth
Research Area: Sociological Methods, Generative AI, Survey Methodology
Discipline: Sociology, Social Science
The study finds that 34% of research participants use generative AI tools like large language models (LLMs) to assist with open-ended survey responses, leading to more homogeneity and positivity in their answers, which could impact data validity by masking social variations.
Methods: The study conducted an original survey on a popular online platform and simulated comparisons between human-written responses from pre-ChatGPT studies and LLM-generated responses.
Key Findings: Use of LLMs by survey participants, differences in text homogeneity, positivity, and masking of social variation in open-ended survey responses.
Citations: 26
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Authors: TS Behrend, RN Landers
Year: 2025
Published in: Journal of Business and Psychology, 2025 - Springer
Institution: University of Nebraska-Lincoln, University of Minnesota
Research Area: LLM in Behavioral Science Research, AI-Assisted Research Methodology
Discipline: Behavioral Science, Psychology, Artificial Intelligence
The paper proposes a framework with five use cases for integrating large language models into survey and experimental research, introduces the Qualtrics-AI Link (QUAIL) tool, and highlights technical and ethical considerations for using LLMs effectively and validly.
Methods: The paper outlines a decision-making framework for five potential uses of LLMs in survey and experimental design, introduces software (QUAIL) for integrating LLM knowledge into Qualtrics, and details technical steps such as prompt engineering, model testing, and validity monitoring.
Key Findings: Applications, implementation strategies, and ethical considerations of large language models in psychological research material development.
DOI: https://doi.org/10.1007/s10869-025-10035-6
Citations: 6
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Authors: S Kwon, NL Kim
Year: 2025
Published in: International Textile and Apparel ..., 2025 - iastatedigitalpress.com
Institution: University of Minnesota
Research Area: Social Media Advertising, Consumer Perception, Information Collection Ethics in Marketing, Social Science.
Discipline: Social Science, Marketing
Consumers are more willing to disclose personal information in social media advertising when they perceive exchanged benefits, such as monetary rewards and personalized recommendations, outweigh the risks; the method of information collection (overt vs. covert) does not significantly affect this decision.
Methods: An online survey was conducted among U.S. Instagram users to assess attitudes toward benefit-risk trade-offs in personal data disclosure for advertising purposes.
Key Findings: Willingness to disclose personal information, click-through intentions, and purchase intentions based on perceived benefits and risks in social media advertisements.
DOI: https://doi.org/10.31274/itaa.18830
Citations: 1
Sample Size: 199
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Authors: G Lee, JY Huh, HY Kim
Year: 2024
Published in: International Textile and Apparel ..., 2024 - iastatedigitalpress.com
Institution: University of Minnesota, Texas Tech University
Research Area: Marketing, Consumer Behavior
Discipline: Textile, Apparel Studies, Marketing, Social Science
DOI: https://doi.org/10.31274/itaa.17436
Citations: 2