Reddit in the Time of COVID

V. Veselovsky, Ashton Anderson
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Abstract

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.
新冠疫情时期的Reddit
当COVID-19大流行袭来时,大部分生活都转移到了网上。所有类型的平台都报告了活动的激增,人们评论了在线平台突然实现的各种重要功能。然而,研究人员对疫情对社交平台的影响缺乏严格的了解,也不清楚这些影响是暂时的还是长期的。我们提出了一个概念框架,用于研究社交平台的大规模演变,并将其应用于Reddit的历史研究,特别关注COVID-19大流行。我们通过两个关键维度来研究平台的演变:结构与内容、宏观与微观层面的分析。结构信号帮助我们量化行为改变了多少,而内容分析则明确了它是如何改变的。在宏观层面上应用这些方法可以揭示整个平台的变化,而在微观层面上,我们研究对个人用户的影响。我们通过展示Reddit在大流行期间经历的非凡和普通的变化来说明这种方法的价值。首先,我们表明,当出现快速增长时,它通常是由少数集中的社区和狭窄的语言使用范围所驱动的。然而,Reddit在2019冠状病毒病期间的增长分布在不同的社区和语言中。其次,所有组的兴趣变化都受到同样的影响,但老用户比新用户更倾向于使用与新冠病毒相关的语言。第三,从兴趣、活跃度和在平台上保持活跃的可能性来看,新一代用户在COVID-19之后到来的新用户浪潮与之前的新用户群体有着根本的不同。这些发现为更严格地了解在线平台在全球大流行期间如何变化提供了帮助。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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