In this work, we examine how fact-checkers prioritize which claims to fact-check and what tools may assist them in their efforts. Through a series of interviews with 23 professional fact-checkers from around the world, we validate that harm assessment is a central component of how fact-checkers triage their work. We also clarify the processes behind fact-checking prioritization, finding that they are typically ad hoc, and gather suggestions for tools that could help with these processes. To address the needs articulated by fact-checkers, we present a structured framework of questions to help fact-checkers negotiate the priority of claims through assessing potential harms. Our FABLE Framework of Misinformation Harms incorporates five dimensions of magnitude---(social) Fragmentation, Actionability, Believability, Likelihood of spread, and Exploitativeness---that can help determine the potential urgency of a specific message or claim when considering misinformation as harm. The result is a practical and conceptual tool to support fact-checkers and others as they make strategic decisions to prioritize their efforts. We conclude with a discussion of computational approaches to support structured prioritization, as well as applications beyond fact-checking to content moderation and curation.

Content moderation research typically prioritizes representing and addressing challenges for one group of stakeholders or communities in one type of context. While taking a focused approach is reasonable or even favorable for empirical case studies, it does not address how content moderation works in multiple contexts. Through a systematic literature review of 86 content moderation articles that document empirical studies, we seek to uncover patterns and tensions within past content moderation research. We find that content moderation can be characterized as a series of tradeoffs around moderation actions, styles, philosophies, and values. We discuss how facilitating cooperation and preventing abuse, two key elements in Grimmelmann’s definition of moderation, are inherently dialectical in practice. We close by showing how researchers, designers, and moderators can use our framework of tradeoffs in their own work, and arguing that tradeoffs should be of central importance in investigating and designing content moderation.

Social media sites use content moderation to attempt to cultivate safe spaces with accurate information for their users. However, content moderation decisions may not be applied equally for all types of users, and may lead to disproportionate censorship related to people's genders, races, or political orientations. We conducted a mixed methods study involving qualitative and quantitative analysis of survey data to understand which types of social media users have content and accounts removed more frequently than others, what types of content and accounts are removed, and how content removed may differ between groups. We found that three groups of social media users in our dataset experienced content and account removals more often than others: political conservatives, transgender people, and Black people. However, the types of content removed from each group varied substantially. Conservative participants' removed content included content that was offensive or allegedly so, misinformation, Covid-related, adult, or hate speech. Transgender participants' content was often removed as adult despite following site guidelines, critical of a dominant group (e.g., men, white people), or specifically related to transgender or queer issues. Black participants' removed content was frequently related to racial justice or racism. More broadly, conservative participants' removals often involved harmful content removed according to site guidelines to create safe spaces with accurate information, while transgender and Black participants' removals often involved content related to expressing their marginalized identities that was removed despite following site policies or fell into content moderation gray areas. We discuss potential ways forward to make content moderation more equitable for marginalized social media users, such as embracing and designing specifically for content moderation gray areas.