The rapid growth of news dissemination and user engagement on social media has raised concerns about the influence and societal impact of biased and unreliable information. As a response to these concerns, a substantial body of research has been dedicated to understanding how users interact with different news. However, this research has primarily analyzed publicly shared posts. With a significant portion of engagement taking place within Facebook's private sphere, it is therefore important to also consider the private posts. In this paper, we present the first comprehensive comparison of the interaction patterns and depth of engagement between public and private posts of different types of news content shared on Facebook. To compare these patterns, we gathered and analyzed two complementary datasets: the first includes interaction data for all Facebook posts (private + public) referencing a manually labeled collection of over 19K news articles, while the second contains only interaction data for public posts tracked by CrowdTangle. As part of our methodology, we introduce several carefully designed data processing steps that address some critical aspects missed by prior works but that (through our iterative discussions and feedback with the CrowdTangle team) emerged as important to ensure fairness for this type of study. Our findings highlight significant disparities in interaction patterns across various news classes and spheres. For example, our statistical analysis demonstrates that users engage significantly more deeply with news in the private sphere compared to the public one, underscoring the pivotal role of considering both the public and private spheres of Facebook in future research. Beyond its scholarly impact, the findings of this study can benefit Facebook content moderators, regulators, and policymakers, contributing to a healthier online discourse.

翻译：社交媒体上新闻传播和用户参与的迅速增长引发了对偏见和不可靠信息影响力及社会影响的担忧。为应对这些关切，大量研究致力于理解用户如何与不同新闻互动。然而，这些研究主要分析了公开分享的帖子。鉴于相当比例的互动发生在Facebook的私密领域，因此考虑私密帖子也至关重要。本文首次对Facebook上分享的不同类型新闻内容在公开与私密帖子中的互动模式和参与深度进行了全面比较。为比较这些模式，我们收集并分析了两个互补数据集：第一个数据集包含所有Facebook帖子（私密+公开）中引用超过19,000篇手动标注新闻文章的互动数据，第二个数据集仅包含CrowdTangle追踪的公开帖子互动数据。作为方法论的一部分，我们引入了若干精心设计的数据处理步骤，解决了先前研究忽略的关键方面——这些方面（通过我们与CrowdTangle团队的反复讨论与反馈）被证明对确保此类研究的公平性至关重要。我们的发现凸显了不同新闻类别和领域在互动模式上的显著差异。例如，统计分析表明，用户在私密领域对新闻的参与深度显著高于公开领域，这强调了未来研究中同时考虑Facebook公开与私密领域的关键作用。除学术影响外，本研究结果还可惠及Facebook内容审核员、监管机构和政策制定者，助力构建更健康的在线话语环境。