When the COVID-19 pandemic hit, much of life moved online. Platforms of all types reported surges of activity, and people remarked on the various important functions that online platforms suddenly fulfilled. However, researchers lack a rigorous understanding of the pandemic's impacts on social platforms, and whether they were temporary or long-lasting. We present a conceptual framework for studying the large-scale evolution of social platforms and apply it to the study of Reddit's history, with a particular focus on the COVID-19 pandemic. We study platform evolution through two key dimensions: structure vs. content and macro- vs. micro-level analysis. Structural signals help us quantify how much behavior changed, while content analysis clarifies exactly how it changed. Applying these at the macro-level illuminates platform-wide changes, while at the micro-level we study impacts on individual users. We illustrate the value of this approach by showing the extraordinary and ordinary changes Reddit went through during the pandemic. First, we show that typically when rapid growth occurs, it is driven by a few concentrated communities and within a narrow slice of language use. However, Reddit's growth throughout COVID-19 was spread across disparate communities and languages. Second, all groups were equally affected in their change of interest, but veteran users tended to invoke COVID-related language more than newer users. Third, the new wave of users that arrived following COVID-19 was fundamentally different from previous cohorts of new users in terms of interests, activity, and likelihood of staying active on the platform. These findings provide a more rigorous understanding of how an online platform changed during the global pandemic.

翻译：当COVID-19疫情暴发时，大量生活活动转向线上。各类平台报告活跃度激增，人们纷纷讨论网络平台突然承担起的各种重要功能。然而，研究者们缺乏对疫情如何影响社交平台及其影响是暂时还是持久性的严格理解。我们提出了一个用于研究社交平台大规模演化的概念框架，并将其应用于Reddit历史的研究，特别聚焦于COVID-19疫情期间。我们通过两个关键维度研究平台演化：结构与内容、宏观与微观分析。结构性信号帮助量化行为变化程度，而内容分析则阐明具体变化方式。将两者应用于宏观层面可揭示平台全域变化，在微观层面则研究对个体用户的影响。通过展示Reddit在疫情期间经历的非凡与寻常变化，我们说明了该方法的价值。首先，我们表明通常快速增长由少数集中社群及狭窄语言使用范围驱动。然而，COVID-19期间Reddit的增长却分散于不同社群和语言中。其次，所有群体在兴趣变化上受到同等影响，但资深用户比新用户更倾向于使用COVID相关语言。第三，疫情后涌入的新用户群体在兴趣、活跃度及持续使用平台的可能性方面，与此前新用户群体存在根本性差异。这些发现为理解在线平台在全球疫情期间的改变提供了更严谨的认知。