Comparing the persuasiveness of role-playing large language models and human experts on polarized U.S. political issues

This repository contains the data and code to support the paper Comparing the persuasiveness of role-playing large language models and human experts on polarized U.S. political issues, authored by Kobi Hackenburg, Lujain Ibrahim, Ben Tappin, and Manos Tsakiris

Repository Content

final_dataset.csv in the data folder is the final processed dataset that is used in the analyses.
The raw_data folder in the data folder contains the raw experiment data.
The messages folder contains the messages generated by GPT-4 and political communication experts.

The code folder contains all the Jupyter Notebooks that were used to generate the analyses and figures in the paper.

To install Python 3, follow these instructions.
To install Pip, follow these instructions.
To install Jupyter Lab/Notebook, follow these instructions. To run Jupyter Lab/Notebook, follow these instructions.
To set up a virtual environment and use it in Jupyter Lab/Notebook, follow these instructions.
To install requirements:

pip install -r requirements.txt

Please contact Lujain Ibrahim or Kobi Hackenburg for any questions regarding this repository or the paper.