Replication Package - Garg and Fetzer (2024)

***********THE REPOSITORY IS PUBLICLY AVAILABLE BUT NOT PUBLICISED YET. PLEASE DO NOT SHARE WIDELY. THE PURPOSE OF THIS REPOSITORY IS PRIMARILY TO ASSIST THE REVIEW PROCESS.*********# Replication Package A repository with replication material for the 2024 working paper by Prashant Garg and Thiemo Fetzer. ## Overview This replication package contains all necessary scripts and data to replicate the main figures and tables presented in the paper. ## Folder Structure ### 1. `1_scripts` This folder contains all scripts required to replicate the main figures and tables of the paper. The scripts are arranged in the order they should be run. - `0_init.Rmd`: An R Markdown file that installs and loads all packages necessary for the subsequent scripts. - `1_fig_1.Rmd`: Produces Figure 1 (Zipf's plots).- `2_fig_2_to_4.Rmd`: Produces Figures 2 to 4 (average levels of expression). - `3_fig_5_to_6.Rmd`: Produces Figures 5 to 6 (trends in expression). - `4_tab_1_to_3.Rmd`: Produces Tables 1 to 3 (descriptive tables). Expected run time for each script is under 2 minutes and requires around 4GB RAM. Script `3_fig_5_to_6.Rmd` can take up to 3-4 minutes and requires up to 6GB RAM. Installation of each package for the first time user may take around 2 minutes each, except 'tidyverse', which may take around 4 minutes. We have not provided a demo since the actual dataset used for analysis is small enough and computations are efficient enough to be run in most systems. Each script starts with a layperson explanation to overview the functionality of the code and a pseudocode for a detailed procedure, followed by the actual code. ### 2. `2_data` This folder contains data used to replicate the main results. The data is called by the respective scripts automatically using relative paths. - `data_dictionary.txt`: Provides a description of all variables as they are coded in the various datasets, especially the main author by time level dataset called `repl_df.csv`.- Processed data at individual author by time (year by month) level aggregated measures are provided, as raw data containing raw tweets cannot be shared. ## Installation Instructions ### Prerequisites This project uses R and RStudio. Make sure you have the following installed: - [R](https://cran.r-project.org/) (version 4.0.0 or later)- [RStudio](https://www.rstudio.com/products/rstudio/download/) Once installed, to ensure the correct versions of the required packages are installed, use the following R markdown script '0_init.Rmd'. This script will install the `remotes` package (if not already installed) and then install the specified versions of the required packages. ## Running the ScriptsOpen 0_init.Rmd in RStudio and run all chunks to install and load the required packages.Run the remaining scripts (1_fig_1.Rmd, 2_fig_2_to_4.Rmd, 3_fig_5_to_6.Rmd, and 4_tab_1_to_3.Rmd) in the order they are listed to reproduce the figures and tables from the paper. # ContactFor any questions, feel free to contact Prashant Garg at [e-mail]. # License This project is licensed under the Apache License 2.0 - see the license.txt file for details.