Data Release for Large Scale, Longitudinal Survey of Large Language Models (LLMs) During the 2024 US Elections Overview This repository contains the questions asked of and responses given by LLMs during the 2024 US elections, collected for a longitudinal survey conducted from July 23, 2024 to November 12, 2024. The study is described in detail in the paper "Large Scale, Longitudinal Study of Large Language Models During the 2024 US Election Season" by Sarah H. Cen, Andrew Ilyas, Hedi Driss, Charlotte Park, Aspen K. Hopkins, Chara Podimata, and Aleksander Madry. As described below and in detail in our paper, 12 LLMs (some of which were equipped with internet access) were queried daily (with the exception of Claude 3 Opus, which was queried weekly) on a fixed set of questions over approximately 4 months. In addition, the same questions were asked of Google search as a baseline. The questions varied by type and topic, and each question was asked multiple times with different prompt variations (e.g., different steering and different instructions). This repository contains the questions, responses, and other relevant documentation as well as sample code. Usage and Quick Start The file s…
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