~/talk

The Echo-Chamber of Your Social Media Feed

Talkat PyData New York City 2019 · 2019-11-04..11-06· [machine-learning]
links:none on file
slides:none on file

Claim: recommendation pipelines on Google YouTube and Facebook concentrate attention and can radicalize rhetoric by surfacing what clicks not what’s comprehensive. Explains crawling, 20+ million new texts per day, indexing into barrels and a lexicon hit list, and quality vs relevance scoring with PageRank math (matrix iteration, average PR = 1, dampener d = 0.85). Shows advertiser bidding via Adwords keyword auctions and thousands of relevance signals so personalized click‑through rates amplify articles into echo chambers.

AI-written summary · about

  1. 0:00Social media algorithms intro
  2. 2:50Search engine indexing
  3. 8:30Data to personalized results
  4. 18:30Rhetoric and click-through rates
  5. 23:46Political echo chambers
  6. 28:02Ethics of search engines
  7. 30:56Q&A: Improving algorithms
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