A social media platform's recommendation algorithm promotes divisive political content because it boosts engagement, even though it increases misinformation and user hostility.

Question

BlackTom AI · Accepted Answer

Consider the scenario described: a platform’s recommendation algorithm boosts divisive political content to drive engagement, which in turn increases misinformation and hostility among users.
Option 1: Source code copyright. This choice addresses legal protections for the software itself, not the social or behavioral effects of the recommendations. It does not explain why divisive content would be amplified or how engagement dynamics contribute to harm, so it’s not a good fit for the described phenomenon.
Option 2: Technical debt. Technical debt refers to the long-term costs incurred by quick or suboptimal design choices, which may affect maintainability or performance. While relevant to engineering, it doesn’t directly capture the mechanism by which harmful content is amplified to boost engagement or the societal harm that results, making it an incomplete explanation here.
Option 3: Data redundancy. Data redundancy concerns duplicate data storage and its implications for efficiency or consistency. Although practical in data architecture, it does not describe how the recommendation system’s optimization for engagement leads to the spread or magnification of harmful content, so this option misses the core issue.
Option 4: Amplification of harm. This phrasing directly addresses the core effect described: the algorithm’s optimization for engagement unintentionally escalates the reach and impact of divisive content, thereby magnifying misinformation and hostility. It captures the causal chain from algorithmic choice to social harm, aligning with the scenario provided.

A social media platform's recommendation algorithm promotes divisive political content because it boosts engagement, even though it increases misinformation and user hostility.单项选择题

类似问题

TikTok’s algorithm considers watch time on videos to decide recommendations.

推荐系统与传统搜索引擎有哪些不同点？（多选题） What are the differences between recommender systems and traditional search engines? Select all that apply

What is a Recommendation Engine used for?

Question at position 10 Vicky explains that everybody's content is different because algorithms identify people's Question Blank 1 of 1[input] from their personal data.

What is a data mining algorithm that analyzes a customer’s purchases and actions on a website and then uses the data to recommend complementary products?

Question at position 10 Which four core components make up YouTube's algorithm?Video Inventory, Signals, Predictions, Ranking FactorsSubscribers, watch time, engagement, qualityWhich four core components make up YouTube's algorithm?Upload time, thumbnail, title, description

Recommendation Blank ______ is a data mining algorithm that analyzes a customer's purchases and actions on a website and then uses the data to recommend complementary products.

What is the primary objective of a social media company's algorithm?

更多留学生实用工具

智能学习助手

风格化写作助手

论文查重助手

文献引用助手

课堂转译助手

课堂笔记助手

Quiz搜索助手

学校历年真题

智能刷题助手

智能匹配练习

希望你的学习变得更简单