arXiv cs.CY· Nicol\`o Pagan, Petter T\"ornberg, Christopher A. Bail, Christopher Barrie·· 11 小时前AI 评分42
LLM 推荐系统通过内容偏好产生人口统计不平等
LLM Recommenders Produce Demographic Inequality Through Content Preferences
AI 导读
一项基于 1000 名受访者 1 万条 Twitter/X 帖子的受控实验发现，LLM 推荐系统仅凭文本就会产生人口统计不平等：模型偏好更长、更负面、更观点鲜明的帖子，尤其是新闻和社会议题类内容，导致被推荐作者的人群构成出现系统性差异。
正文 · 原文
Abstract:Large language models (LLMs) are increasingly being integrated into systems that rank and recommend online content. We examine how this shift can produce demographic inequality in whose voices are surfaced. Using 10,000 Twitter/X posts written by 1,000 survey respondents and linked to verified self-reported characteristics across nine demographic attributes, we conduct a controlled recommendation experiment across three LLM providers, six recommendation objectives, and five levels of contextual information. By varying whether models receive post text alone, platform metadata, or explicit author demographics, we isolate three pathways to unequal recommendation: preferences for demographically patterned content, reliance on unequal engagement signals, and direct use of disclosed identity. We find that demographic inequality emerges from text alone. Models consistently favour longer, more negative, and more opinionated posts, particularly those concerning news and social issues, producing systematic differences in the demographic composition of recommended authors. Platform metadata generally amplifies these inequalities, while explicitly disclosing authors' demographic characteristics produces little additional change. Recommendation objectives mainly affect the magnitude of these patterns: controversial framing intensifies both content and demographic skew, whereas popularity-oriented framing dampens it, although for some attributes - most notably age - the objective can also reverse which group is favoured. LLM-based recommenders can therefore reproduce demographic inequality by proxy, not through explicit demographic targeting, but through preferences for content and engagement signals already structured by social inequality.
| Subjects: | Computers and Society (cs.CY); Social and Information Networks (cs.SI) |
| Cite as: | arXiv:2610.41854 [cs.CY] |
| (or arXiv:2610.41854v1 [cs.CY] for this version) | |
| https://doi.org/10.48550/arXiv.2610.41854 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Nicolò Pagan Mr. [view email]
[v1]
Fri, 30 Oct 2026 15:11:08 UTC (5,878 KB)
来源：arXiv cs.CY · arxiv.org