Why Does TikTok Know What You Like?

An interactive 15-minute lesson on recommendation systems for HKBU MCCP6010, Group 6.

Why Does TikTok Know What You Like? is an interactive lesson created for HKBU MCCP6010 · Group 6. It introduces recommendation systems through familiar video-feed examples and a four-step journey: collect signals, understand content, rank videos, and update recommendations.

Two illustrated video feeds introducing the lesson on user signals, content, ranking, and feedback
A 15-minute learning journey from viewing behavior to the next recommended video.

What It Covers

  • User signals: Compare explicit feedback, such as likes and follows, with viewing behavior, such as watch time, skips, and rewatches.
  • Content clues: Explore how topics, captions, hashtags, sounds, and shared interests can help identify candidate videos.
  • Ranking and feedback: Calculate scores using a simplified classroom rule, explain a ranking, and see how new feedback can change the order.
  • Exploration and feed controls: Discuss how repeated recommendations may narrow exposure and how viewers can influence their feeds.

Interactive Features

The lesson combines step-by-step reveals, worked examples, pair discussions, timed activities, and a closing three-question quiz. Presentation tools include keyboard navigation, a page overview, speaker notes, fullscreen mode, and print-to-PDF support. The closing quiz supports configurable Kahoot links and an on-screen fallback.

The feeds, scores, and updates are classroom illustrations. The ranking rule is a teaching model rather than TikTok’s disclosed algorithm.

Tech Stack

HTML, CSS, JavaScript, SVG illustrations, and browser-based presentation tools.

Interactive Lesson · GitHub

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