Social media platforms enhance the propagation of online misinformation by providing large user bases with a quick means to share content. One way to disrupt the rapid dissemination of misinformation at scale is through warning tags, which label content as potentially false or misleading. Past warning tag mitigation studies yield mixed results for diverse audiences, however. We hypothesize that personalizing warning tags to the individual characteristics of their diverse users may enhance mitigation effectiveness. To reach the goal of personalization, we need to understand how people differ and how those differences predict a person's attitudes and self-described behaviors toward tags and tagged content. In this study, we leverage Amazon Mechanical Turk (n = 132) and undergraduate students (n = 112) to provide this foundational understanding. Specifically, we find attitudes towards warning tags and self-described behaviors are positively influenced by factors such as Personality Openness and Agreeableness, Need for Cognitive Closure (NFCC), Cognitive Reflection Test (CRT) score, and Trust in Medical Scientists. Conversely, Trust in Religious Leaders, Conscientiousness, and political conservatism were negatively correlated with these attitudes and behaviors. We synthesize our results into design insights and a future research agenda for more effective and personalized misinformation warning tags and misinformation mitigation strategies more generally.

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