Abstract

Feed ranking algorithms select and prioritize what users see from a vast inventory of content on social media. They greatly impact people's opinions, moods, and actions. Typically trained to maximize user engagement (e.g., likes, replies, and reposts), feed ranking algorithms are often blamed for exacerbating negative societal outcomes, like political polarization and toxic speech online. Until recently, running feed ranking experiments and studying the effects of feed ranking algorithms was only possible from inside social media companies. However, the emergence of middleware-based feed reranking infrastructure and more customizable platforms like Bluesky have created new opportunities for experimentation. This tutorial aims to introduce participants to these new experimental opportunities and provide a practical guide for conducting feed-ranking experiments through a mix of lectures, a case study, and hands-on exercises.

📅 Day: Tuesday, July 28, 2026
🕜 Time: 1:00 PM - 4:00 PM
📍 Location: Mansfield (210)

Schedule

1. History & foundations (50 mins)
2. Feed experiments using middlewares (50 mins)
3. Hands-on exercises (1 hour)
• Modify feeds with a browser extension
• Build your own BlueSky feed

Prerequisites

• Familiarity with Python and HTTP APIs.
• We recommend having a Bluesky account.

Resources

Slides: [Part 1] History & foundations, [Part 2] Feed experiments using middlewares.
Hands-on execises: https://github.com/social-media-ais/ic2s2-26-tutorial-code