Instagram Platform Mechanics
Feed, Reels, Stories, and the grid as identity. Hashtags and keyword SEO, share-driven distribution.
- Lectures
- 8
- Total runtime
- 3h 21m
- Attendance minimum
- 1h 41m
- Prerequisites
- None
Lecture Playlist
Ordered as a teaching progression, not by popularity. Attendance is recorded once half of a lecture has been watched.
- The End of Competition? (Marco Iansiti) What kind of company decides your reach: software, data and algorithms at the core 13 min Attended
- Data, network effects, and competitive advantage | Andrei Hagiu Why the ranking gets better the more everyone uses it: data-enabled learning, not just network effects 9 min Attended
- Stanford Seminar: Making Sense of Algorithms in News Feeds The feed is a filtered subset, not a timeline — and it is invisible to the people reading it 51 min Attended
- Stanford XCS224U: NLU I Information Retrieval, Part 1: Guiding Ideas I Spring 2023 Search as a ranking problem: queries, documents, and what "relevant" means to a machine 18 min Attended
- Stanford XCS224U: NLU I Information Retrieval, Part 2: Classical IR I Spring 2023 Why the literal words matter: term matching, rare-term weighting, and vocabulary mismatch 15 min Attended
- The Hype Machine | Sinan Aral Share-driven distribution: how a send actually moves content, and how influence is measured 69 min Attended
- Visual Marketing and the Science Behind Brand Identity and Consumer Attention The grid as identity: visual consistency, fluency, and what a profile communicates at a glance 16 min Attended
- Practicum · working creator How to grow on Instagram (according to Instagram) in 2025 Refusing to guess: a working Instagram creator rebuilding her distribution strategy out of the platform's own published statements, hashtags included 10 min Attended
Every course reserves one practicum seat, listed last and marked P. It is filled by someone who has shipped the work — here, Jade Beason — because the university lectures establish why something works and the practicum shows it being done under real constraints.