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The rapid growth of news dissemination and user engagement on social mediahas raised concerns about the influence and societal impact of biased andunreliable information. As a response to these concerns, a substantial body ofresearch has been dedicated to understanding how users interact with differentnews. However, this research has primarily analyzed publicly shared posts. Witha significant portion of engagement taking place within Facebook's privatesphere, it is therefore important to also consider the private posts. In thispaper, we present the first comprehensive comparison of the interactionpatterns and depth of engagement between public and private posts of differenttypes of news content shared on Facebook. To compare these patterns, wegathered and analyzed two complementary datasets: the first includesinteraction data for all Facebook posts (private + public) referencing amanually labeled collection of over 19K news articles, while the secondcontains only interaction data for public posts tracked by CrowdTangle. As partof our methodology, we introduce several carefully designed data processingsteps 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 findingshighlight significant disparities in interaction patterns across various newsclasses and spheres. For example, our statistical analysis demonstrates thatusers engage significantly more deeply with news in the private sphere comparedto the public one, underscoring the pivotal role of considering both the publicand private spheres of Facebook in future research. Beyond its scholarlyimpact, the findings of this study can benefit Facebook content moderators,regulators, and policymakers, contributing to a healthier online discourse.

Understanding Differences in News Article Interaction Patterns on Facebook: Public vs. Private Sharing with Varying Bias and Reliability