Cactool 0.5.7.4

An easy way to collaboratively code social media posts for manual content and discourse analysis

Cactool

Introduction

Cactool is a platform developed for researchers to collaboratively and manually code pre-existing datasets of social media posts for content and discourse analysis. After the initial setup, getting started is easy: import a csv of social media URLs; set your coding variables; and grant access to your coders who can get started right away.

• No more coding via spreadsheets Coding is undertaken via your browser (tested working on Chrome, Firefox, Edge, & Safari) with posts visible as they would be on the social media platform. This allows your coders to evaluate social media content in their native format.
• Simple Import and Export Take your pre-existing social media URLs from software such as NodeXL, or API Scrapers such as Tweepy and import them as a CSV list. When done, you can export your data via CSV to whatever analysis software you desire.
• Works for multiple social media platforms Cactool currently works with URLs from Twitter, Instagram, YouTube, & TikTok.
• Manage Multiple Datasets Want to split your project by source/themes? You can manage multiple concurrent datasets at the same time.
• Built for collaboration Cactool comes pre-packaged with user management; codes attributed are attributed to each coder for coder reliability calculation (such as ReCal). Multiple people can be coding at the same time without sharing documents. No need to worry about version control or splitting up data.
• Code on the Go Cactool is mobile friendly and can be accessed remotely (we recommend using a VPN to connect, see our tutorial for why). This provides researchers interested in social media content and spaciality new avenues of research.

Documentation

Easy to follow installation instructions and user guides can be found via the documentation on Read the Docs

Installation and usage

1. Install Cactool

pip install cactool

2. Start the website

cactool

Credits

The project’s Principle Investigator is Dr Liam McLoughlin, Lecturer in Politics at the University of Manchester, and the development was undertaken by Sam Ezeh

Citations

Bibtex

@software{McLoughlin_Ezeh_2022,
  title = {{Cactool: An easy way to collaboratively code social media posts for manual content and discourse analysis (BETA)}},
  author  = {McLoughlin, Liam and Ezeh, Sam},
  year  = {2022},
  doi = {10.5281/zenodo.6070206},
  url = {https://github.com/cactool/cactool},
  license = {MIT}
}

APA

McLoughlin, L., & Ezeh, S. (2022). Cactool: An easy way to collaboratively code social media posts for manual content and discourse analysis (BETA). [Computer software]. URL:https://github.com/cactool/cactool

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