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Social Media Scrolling Virality Addon 60 V2

Master Social Media Scrolling Virality Addon 60 V2 with 60 free flashcards. Study using spaced repetition and focus mode for effective learning in Marketing.

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SM: What is a “candidate set” in feed ranking?

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The shortlist of posts/videos retrieved for you before final ranking decides what gets shown next.

SM: What is “retrieval” in recommendation systems (simple)?

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The step that quickly finds potentially relevant items from a huge catalog before more expensive ranking.

SM: Why do platforms use multiple stages (retrieval → ranking)?

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To scale: retrieval narrows billions of items to thousands; ranking then scores the shortlist more precisely.

SM: What is a “feature” in ML ranking models?

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An input variable used to predict outcomes (e.g., your recent watches, video length, creator relationship).

SM: What is “label leakage” (high level) in ranking experiments?

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When a feature indirectly includes future information (or the target itself), making offline results look great but failing in production.

SM: What is “proxy gaming” in social algorithms?

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When creators optimize for a measurable proxy (watch time) in ways that don’t improve true value (satisfaction).

SM: Why do platforms care about “regret” or “I didn’t want this” signals?

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Because high engagement can still be harmful; regret signals help balance retention against long-term satisfaction.

SM: What is “satisfaction gap” content?

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Content that gets clicks/attention but leaves viewers feeling worse or misled, hurting long-term trust.

SM: What is “diversity” in feed ranking?

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Deliberately mixing topics, creators, and formats so your feed doesn’t become repetitive or overly narrow.

SM: What is “novelty vs relevance” tradeoff?

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Novel items feel fresh but may be less relevant; relevant items match known interests but can become boring over time.

SM: What is “recency bias” in social engagement?

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People respond more to recent posts; platforms incorporate time decay so new items can compete with older winners.

SM: What is time decay in ranking?

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A mechanism that gradually lowers the score of older content unless it keeps earning strong engagement.

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