In the online information ecosystem, a content label is an attachment to a piece of content intended to contextualize that content for the viewer. Content labels are information about information, such as fact‐checks or sensitive content warnings. Research into content labeling is nascent, but growing; researchers have made strides toward understanding labeling best practices to deal with issues such as disinformation, and misleading content that may affect everything from voting to health. To make this review tractable, we focus on compiling the literature that can contextualize labeling effects and consequences. This review summarizes the central labeling literature, highlights gaps for future research, discusses considerations for social media, and explores definitions toward a taxonomy. Specifically, this article discusses the particulars of content labels, their presentation, and the effects of various labels. The current literature can guide the usage of labels on social media platforms and inform public debate over platform moderation.

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Local news sources in the United States have been dwindling for years. Although newsrooms are shrinking, the American public generally trust their local news sources. Crisis events like the COVID-19 pandemic are circumstances where people are actively searching for information and some of what they will find will inevitably be misinformation given the volume of misinformation being created and the affordances of social media services that encourage viral spread. It is critical to understand if local news is spreading misinformation or acting as a crosscutting information source. This study uses local news data from a media aggregator and mixed methods to analyze the relationship between local news and misinformation. Findings suggest that local news sources are serving as cross-cutting information sources but occasionally reinforce misinformation. We also find a worrying increase of anti-mask stories and accompanying decrease of pro-mask stories after a mask mandate is enacted.

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