Large language models (LLMs) may not equitably represent diverse global perspectives on
societal issues. In this paper, we develop a quantitative framework to evaluate whose
opinions model-generated responses are more similar to. We first build a dataset,
GlobalOpinionQA, comprised of questions and answers from cross-national surveys
designed to capture diverse opinions on global issues across different countries. Next, we
define a metric that quantifies the similarity between LLM-generated survey responses and …