Experimental Evidence that Network Structure, Not Homophily Governs Vulnerable Populations’ Susceptibility to Online Disinformation
This github contains the reproduction materials (including code and data) for Centola et. al. 2025, "Experimental Evidence that Network Structure, Not Homophily Governs Vulnerable Populations’ Susceptibility to Online Disinformation"
This software has been tested on macOS Sequoia (15.5), using R version 4.4.1. However, it should work on any system with R (and the below packages) installed.
CI-Vax requires the following R packages (listed: the version on which the package was tested):
- DescTools (0.99.57)
- dplyr (1.1.4)
- ggpattern (1.1.1)
- ggplot2 (3.5.1)
- ggpubr (0.6.0)
- grid (4.4.1)
- gridBase (0.4.7)
- igraph (2.0.3)
- lmtest (0.9.40)
- maps (3.4.2)
- mvtnorm (1.3.1)
- sandwich (3.1.1)
- sf (1.0.18)
- tidyverse (2.0.0)
- usmap (0.7.1)
- viridis (0.6.5)
This software package (and included data) can be downloaded from the NDG website (https://ndg.asc.upenn.edu/) or cloned from github:
git clone https://github.com/billwpierce/ci-vax.git
cd ci-vax
Instructions to reproduce the results from the paper. R files can be run using Rscript {file_name.R}
- Run CI-VAX_Final.R
- Run stats_fig5.R
- Optional: Update lines 217-221 of figure-5.R
- While these values should match the values currently listed in the software, these values can be checked against the outputs of CI-VAX_Final.R and stats_fig5.R
- The terminal output of stats_fig5.R will include a table of outputs. Copy the values from the column labeled "grand_mean_ind" into the relevant variables in figure-5.R (lines 218, 219, 221, and 221).
- CI-VAX_Final.R will output the average individual error change for both egalitarian and centralized networks, the values of which should be placed in lines 217 and 220, respectively.
- Run figure-5.R
- Run figure-S9a.R and figure-S9b.R
The outputs of these files contain the statistical tests from the paper, while the paper's figures can all be found under the "figures" folder.
In order to reproduce the results for LIWC-22, the LIWC/Network Level Data.csv and LIWC/Sentence Level Data.csv can be separately imported, and re-ran, on the LIWC software (https://www.liwc.app/). The outputs from this software can replace the "LIWC-22 Results" data for reproduction.
- Using LIWC-22 requires the purchase of a license; as such, the LIWC outputs for this specific chat data are included with this download.
- LIWC-15 is no longer actively supported; for completeness, our prior outputs from LIWC-15 are nevertheless included here.
Once the LIWC result files are updated, their statistical output comes with the output of CI-VAX_Final.R.
CI-Vax_Final.R and figure-5.R should both run relatively quickly on modern hardware (< 30 seconds apiece), while stats_fig5.R, figure-S9a.R and figure-S9b.R all run simulations: as such, they take longer (~2-10 minutes apiece) to run on typical hardware.