#survey-research News & Analysis

4 articles tagged with #survey-research. AI-curated summaries with sentiment analysis and key takeaways from 50+ sources.

4 articles

AIBearisharXiv – CS AI · 4d ago6/10

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Overstating Attitudes, Ignoring Networks: LLM Biases in Simulating Misinformation Susceptibility

Researchers found that large language models fail to accurately simulate human susceptibility to misinformation, consistently overstating how attitudes drive belief and sharing while ignoring social network effects. The study reveals systematic biases in how LLMs represent misinformation concepts, suggesting they are better tools for identifying where AI diverges from human judgment rather than replacing human survey responses.

AIBearisharXiv – CS AI · Mar 36/106

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Stochastic Parrots or Singing in Harmony? Testing Five Leading LLMs for their Ability to Replicate a Human Survey with Synthetic Data

Researchers compared human survey responses from 420 Silicon Valley developers with synthetic data from five leading LLMs including ChatGPT, Claude, and Gemini. While AI models produced technically plausible results, they failed to capture counterintuitive insights and only replicated conventional wisdom rather than revealing novel findings.

AINeutralarXiv – CS AI · Mar 264/10

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A Comprehensive Survey on Enterprise Financial Risk Analysis from Big Data and LLMs Perspective

A comprehensive survey paper examines enterprise financial risk analysis from Big Data and large language models perspectives, systematizing existing research methods and identifying future investigation directions. The paper addresses gaps in current surveys by providing a holistic synthesis of AI-driven approaches to financial risk prediction.

AINeutralarXiv – CS AI · Mar 44/103

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Psychometric Item Validation Using Virtual Respondents with Trait-Response Mediators

Researchers developed a framework using large language models to simulate virtual respondents for validating psychometric survey items, addressing the challenge of ensuring construct validity without costly human data collection. The approach uses trait-response mediators to identify survey items that robustly measure intended psychological traits across three major trait theories.