Misinformation-replication

Replication files for "Optimal Policies to Battle the Coronavirus 'Infodemic' Among Social Media Users in Sub-Saharan Africa."

• Pre-registration here.

Files

• code/ folder
  • Data cleaning script dataCleaning_evaluation.Rmd
  • Analysis scripts
  • misinformation_replication.Rmd (both learning and evaluation primary analysis)
    • Depends on utils.R
  • misinformation_replication_secondary.Rmd(both learning and evaluation secondary analysis)
    • Depends on utils.R

Reproducing results

Python is required to generate the contextual probabilities, but a copy of the probabilities is saved in this replication repository. R is required for primary analysis

1. Save most recent data in the data/ folder.
2. Generate contextual probabilities for adaptive weights for inference:
   • You may wish to create a conda environment: code/installations.md
   • Run code/contextual_probabilities/gen_probabilities.py
   • Depends on code/contextual_probabilities/utils.py
   • Generates data/contextual_probabilities.npy
   • Run code/contextual_probabilities/convert_contextual_probs.R to convert numpy object to rds
   • Generates code/objects/contextual_probabilities.RDS
3. To replicate analysis, run
   • code/misinformation_replication.Rmd (primary analysis in paper)
     • Depends on utils.R
   • code/misinformation_replication_secondary.Rmd (secondary analysis)
     • Depends on utils.R
4. Resulting html files (misinformation_replication.html, misinformation_replication_secondary.html) will be saved in the same folder.
5. Figures and latex tables will be saved in figures/ and tables/ folders respectively.