Social bots spoil activist sentiment without eroding engagement

This repository contains the code and data required to replicate the results presented in the article:
Li, L., Vasarhelyi, O., & Vedres, B. (2024). Social bots sour activist sentiment without eroding engagement. Scientific Reports, forthcoming.

It is designed to provide a straightforward replication process for the primary findings discussed in the paper.

Contents

• Code: All the scripts used to conduct the analyses presented in the main text.
• Data: Processed datasets necessary for replication.
• Svg: Figures that appear in the main text.

Directory Structure

.
├── analysis
├── bot_detection
├── data
│   ├── cascade_analysis_data
│   ├── for_cascade_vis
│   ├── for_pred_vis
│   └── regression_data
├── data_collection
│   ├── create_matching
│   └── get_full_cascade_timeline
└── svg

Description of Folders

• analysis: Contains scripts and notebooks used for analyzing the data and generating results reported in the article.
• bot_detection: Houses code and models related to the detection of bot accounts within the dataset.
• data: This folder includes various datasets used throughout the analysis.
  • cascade_analysis_data: Data specifically prepared for analyzing cascades of retweets and interactions.
  • for_cascade_vis: Datasets intended for visualization of cascade patterns.
  • for_pred_vis: Data used for visualizing predictive models and their outputs.
  • regression_data: Contains the data used in regression analyses.
• data_collection: Scripts and processes used to collect and prepare the data for analysis.
  • create_matching: Code to create treated and matched sample for analysis.
  • get_full_cascade_timeline: Scripts that compile timelines of retweet cascades for analysis.
• svg: This directory contains visualizations included in the article.

How to Use

1. Clone or download the repository.
2. Follow the instructions in the provided scripts for replication of the main analyses.
3. The data included here is a minimal subset required for replicating the key results.

Important Notes

• This repository only includes the data and code relevant to the main text of the article.
• Additional materials, such as the supplementary information (SI), raw data, and extended analysis scripts, are not included due to their size and complexity.
• If you require access to the raw data, supplementary materials, or other extended analyses, please feel free to contact the repository owner directly, or the corresponding author at vedresb@ceu.edu.