This repository contains the code for the analysis and results in the manuscript Computational analysis of US congressional speeches reveals a shift from evidence to intuition

• We developed the codes in this repository with Python (3.6.13) and R(4.3.1) on Ubuntu 20.04.

• The scripts are numbered in the order in which the results in the paper are presented with results saved in the output directory.

• The aggregated EMI score and data for variables required to make plots and run statistical analysis are in this repository under the data directory.

• For the code in the directory compute_EMI to execute, the required Congressional speeches and embedding model are in a separate OSF repository, because of their size.

  • The Python package dependencies for the scripts in the directory compute_EMI can be installed using the requirements.txt file i.e., pip install -r requirements.txt.
  • To compute the EMI score on the Congressional speeches, run the script label_filtered_uscongress_congress_word2vec.sh from within the compute_EMI directory.

  For questions or clarifications please contact:

  • Segun Aroyehun ([email protected])
  • David Garcia ([email protected])

@article{aroyehun2024computational,
  title={Computational analysis of US Congressional speeches reveals a shift from evidence to intuition},
  author={Aroyehun, Segun Taofeek and Simchon, Almog and Carrella, Fabio and Lasser, Jana and Lewandowsky, Stephan and Garcia, David},
  journal={arXiv preprint arXiv:2405.07323},
  year={2024}