Accurate information about emergency contraception (EC) is integral to reproductive autonomy, especially within the current national landscape restricting reproductive rights and health. Yet there is substantial misinformation about EC that may undermine its use, leading to adverse and consequential outcomes. Social media use is ubiquitous in the US across all demographic groups and is a widespread and influential source for sexual and reproductive health (mis)information, particularly among people of reproductive age. Limited empirical evidence is available investigating the quality of information about EC on social media platforms. Social media can be a powerful source for surveillance efforts to identify and track EC misinformation. Yet the pace of social media platform evolution far outpaces conventional surveillance efforts. Innovative, interdisciplinary approaches are needed to gain a more comprehensive understanding of the social media information ecosystem and to track real-time, current information quality and discourse across social media platforms that reflect broader societal trends. We therefore propose an novel, translational, community-engaged, three-phase mixed methods study in collaboration with the American Society for Emergency Contraception. It will assess information quality, post characteristics, and leverage a hybrid human- and computational approach to build the TRUST-EC classifier to identify misinformation, which after further testing, will be an innovative method for surveilling EC misinformation across social media platforms. This research is actionable and scalable, with the ability to expand its application to other contraceptive methods, making it of enduring relevance.