揭示低资源语言健康信息搜索中的数据边界现象
Into the Void: Understanding Online Health Information in Low-Web Data Languages
- 提出'数据边界'概念,分析算法在低语种下的失效机制
- 发现健康搜索结果常偏离查询,多为营养与宗教内容
- 适合关注数字公平与信息可及性的研究者阅读
数据空白——互联网中可靠信息稀缺或缺失的区域——对在线健康信息获取构成重大挑战,尤其针对使用低网络数据语言的用户。这些空白不仅出现在传统搜索引擎中,更在社交平台日益演变为非正式搜索入口的背景下浮现。本文引入‘数据边界’概念:算法结构开始削弱搜索结果相关性与可信度的关键阈值。不同于数据空白核心常被不良行为者利用传播虚假信息,数据边界是语言代表性不足、算法放大效应与社会文化错配等系统性因素共同导致的信息不稳定空间。以提格雷尼亚语和阿姆哈拉语为例,我们评估了健康查询的搜索结果共性、信息质量与可信度,以及结果与查询偏离特征。研究发现,低语种健康搜索结果未必以查询语言呈现,且常被营养与宗教建议主导。结果偏离主要源于算法失败、无意操纵或内容创作者主动操控。我们据此揭示数据边界在多重信息可得性约束下的具体表现。
原文摘要 · Abstract (English)
Data voids--areas of the internet where reliable information is scarce or absent--pose significant challenges to online health information seeking, particularly for users operating in low-web data languages. These voids are increasingly encountered not on traditional search engines alone, but on social media platforms, which have gradually morphed into informal search engines for millions of people. In this paper, we introduce the phenomenon of data horizons: a critical boundary where algorithmic structures begin to degrade the relevance and reliability of search results. Unlike the core of a data void, which is often exploited by bad actors to spread misinformation, the data horizon marks the critical space where systemic factors, such as linguistic underrepresentation, algorithmic amplification, and socio-cultural mismatch, create conditions of informational instability. Focusing on Tigrinya and Amharic as languages of study, we evaluate (1) the common characteristics of search results for health queries, (2) the quality and credibility of health information, and (3) characteristics of search results that diverge from their queries. We find that search results for health queries in low-web data languages may not always be in the language of search and may be dominated by nutritional and religious advice. We show that search results that diverge from their queries in low-resourced languages are due to algorithmic failures, (un)intentional manipulation, or active manipulation by content creators. We use our findings to illustrate how a data horizon manifests under several interacting constraints on information availability.
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