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Opinions and Gaze Coordination: Code for Paxton, Richardson, & Dale (submitted)

This repo contains code for the analyses presented in our article, "Seeing the other side: Conflict and controversy increase gaze coordination" (Paxton, Dale, & Richardson, submitted).


The repo contains separate directories for analysis files, figures, and supplementary code.

  • analyses: Directory of Jupyter notebooks:
    • 00-oag-data_cleaning.ipynb: Notebook with Python kernel. Converts participant numeric IDs to sequential numeric IDs, with listeners starting at 00001 and speakers starting at 99991.
    • 01-oag-data_cleaning.ipynb: Notebook with Python kernel. Converts raw output files into more manageable formats.
    • 02-oag-data_preparation.ipynb: Notebook with R kernel. Cleans the data and outputs analysis-ready files.
    • 03-oag-data_analysis.ipynb: Notebook with R kernel. Performs analysis over processed and cleaned data. Includes aggregated code output to show work for those who cannot access the raw data from ICPSR.
  • supplementary-code: Directory of R and Python scripts called by the notebooks.
  • figures: Directory of figures produced by 01-oag-data_analysis.ipynb.

Related materials

Data for the project are available to verified researchers through ICPSR. The determination to make these data openly available only to researchers was made by the original ethical governing body for the study (the Institutional Review Board at the University of California, Merced), in keeping with the approved IRB protocol and the informed consent signed by participants. A link to the data deposit will be made available once the deposit is accepted by ICSPR. You can find more about ICSPR's restricted-use data policies on their website.

Notes on running and viewing

Static notebooks may be viewed in your browser. In order to interact with the notebooks, you will need to download them to your computer; in order to execute them, you will need to download the data from ICPSR (again, in accordance with their restricted-use data policies) as well.

For those unfamiliar with Jupyter notebooks, we recommend taking a look at Project Jupyter's documentation and FAQ before getting started. (Be sure to have Jupyter installed first.)