DOI: 10.5281/zenodo.12169423
title: Replication Package - Garg and Fetzer (2024)

description: ***********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 prashant.garg@imperial.ac.uk.

# License

This project is licensed under the Apache License 2.0 - see the license.txt file for details.