The model of the attention economy, where content producers compete for the attention of users, relies on two key forces: information supply and demand. This study leverages the feedback loop between these forces to develop a method for detecting and quantifying information voids, i.e., periods in which little or no reliable information is available on a given topic. Using a case study on COVID-19 vaccines rollout in six European countries, and drawing on data from multiple platforms including Facebook, Google, Twitter, Wikipedia, and online news outlets, we examine how information voids emerge, persist and correlate with a decline in the proportion of high-quality information circulating online. By conceptualising information voids as a specific regime of information spreading, we also quantify their counterpart, information overabundance, which constitute a central component of the current definition of infodemic. We show that information voids are associated with a higher prevalence of misinformation, thus representing problematic hotspots in which individuals are more likely to be misled by low-quality online content. Overall, our findings provide empirical support for the inclusion of information voids in mechanistic explanations of misinformation emergence.

翻译：注意力经济模型——内容生产者争夺用户注意力的运作机制——依赖于两大核心驱动力：信息供给与需求。本研究通过利用这两股力量之间的反馈循环，开发了一种检测与量化信息真空的方法，即特定主题上可靠信息稀缺或缺失的时期。以六个欧洲国家的新冠疫苗推广为案例，结合来自Facebook、Google、Twitter、维基百科及在线新闻媒体的多平台数据，我们分析了信息真空如何形成、持续，并与网络高质量信息比例下降相关联。通过将信息真空概念化为信息传播的一种特定状态，我们也量化了其对应现象——信息过载，这构成了当前"信息疫情"定义的核心组成部分。研究表明，信息真空与错误信息的高发率相关，从而成为个体更易受低质量网络内容误导的问题热点。总体而言，我们的研究结果为在错误信息产生的机制性解释中纳入信息真空提供了实证支持。