We are pleased to announce the release of the new Reddit Historical Data Collector in Communalytic, a no-code computational social science research tool for studying online communities and discourse. Both new and existing Communalytic users can now collect historical Reddit data (posts and meta data).
This new data collector uses the official Reddit API and can support keyword-based search for relevant submissions. Edu users can collect up to 200 recent submissions + corresponding comments and replies for a given public subreddit and Pro users can collect up to 900 submissions + comments and replies.
In addition to Reddit, Communalytic can also collect, analyze, and visualize publicly available data from other social media platforms including Telegram, YouTube, Facebook/Instagram (via CrowdTangle), and Twitter, or from a user-uploaded CSV or JSON file.
The Edu version is free to use and is designed to help students learn about social media data analytics and social network analysis. The PRO version is designed for the academic research community and is ideal for large-scale academic research projects. It provides researchers with the resources and infrastructure necessary for conducting independent research in the public interest.
The tool is released as part of our work developing research tools, techniques, and visualization dashboards to support computational social science research. Communalytic contains a suite of advanced built-in data analytics modules including a Toxicity Analyzer, a Sentiment Analyzer, a Topic Analyzer and a built-in Network Analyzer. These modules can be used to automatically:
- detect anti-social interactions (i.e., harassment, hate speech, extremist content, etc.),
- assess sentiments in online discourse,
- identify and group together social media posts that are semantically similar and identify latent topics within your dataset,
- generate and visualize various types of networks, including communication and link-sharing networks, which in turn can be used to identify influencers, map shared interests among online actors, study the spread of mis/dis-information and detect signs of possible coordination among seemingly disparate actors.
For more details, see Communalytic’s Tutorials page.