---
id: "prereq-social-media-algorithms"
type: "prereq"
source_timestamps: ["\\\"§ Leverage Real-time", "Data-based Customer Insights\\\""]
tags: ["algorithms", "social-media"]
related: ["concept-algorithmic-resource-matching", "entity-product-tiktok"]
reason: "Required to grasp the 'algorithmic resource matching' concept applied to physical supply chains."
sources: ["attention"]
sourceVaultSlug: "hbr-seg-attention"
originDay: 4
articleStem: "hbr-foci-68-popmart-attention-economy"
sourceUrl: "https://hbr.org/2025/07/how-pop-mart-won-young-customers-in-a-fragmented-attention-economy"
sourceTitle: "How Pop Mart Won Young Customers in a Fragmented Attention Economy"
---
# Understanding of Social Media Recommendation Algorithms

**Prerequisite.** A working understanding of how social media recommendation algorithms operate.

**Why it matters.** [[entity-yang-li|The author]]'s core analogy relies on the reader understanding how platforms like [[entity-product-tiktok|TikTok]] use engagement metrics (shares, likes, completion rates) to automatically channel traffic and amplify content visibility. Required to grasp the [[concept-algorithmic-resource-matching|'algorithmic resource matching']] concept applied to physical supply chains and the [[framework-algorithmic-product-lifecycle|Algorithmic Product Lifecycle]].

**Enrichment pointer.** For depth, see research on TikTok/algorithmic feeds and recommendation systems, and Herbert Simon's attention-economy framing (attention as the scarce resource these algorithms compete for).