For Teaching & Learning
Communalytic is a computational social science research tool
for studying online communities and discourse.
An easy-to-use social media data collector designed to collect publicly available data from Reddit, Telegram, YouTube, Facebook/ Instagram (via CrowdTangle) and Twitter, or you can import your own CSV or JSON data files - No coding required
An AI-powered toxicity analysis module designed to identify toxic and anti-social interactions in online discourse - Users can choose from two different AI toxicity detection systems: Detoxify or Perspective
A lexicon and rule-based sentiment analysis module designed to detect the polarity of text in a dataset - Users can choose from 3 different sentiment analysis libraries: VADER (EN), TextBlob (EN, FR, DE), or Dostoevsky (RU)
[NEW] An AI-powered module designed to automatically identify and group together social media posts that are semantically similar using embeddings - No prior knowledge of the dataset is required
Communalytic EDU is designed to help students learn about social media data analytics.
EDU Account Type/Capacity
EDU Data Sources
Communalytic PRO is designed for the academic research community and is ideal for large-scale research projects.
PRO Account Type/Capacity
PRO Data Sources
Case Studies and Tutorials
New to Communalytic? We have prepared a number of tutorials to help you get started.
Social Media Lab’s Computational Social Science (CSS) Bootcamp – Video recordings + Slides
How to Cite:
If you are using Communalytic in an academic publication, please cite us as:
Gruzd, A., & Mai, P. (2023). Communalytic: A Research Tool For Studying Online Communities and Online Discourse. Available at https://Communalytic.org