Aging dams are numerous across the Hudson Valley, creating infrastructure management challenges, safety risks, and widespread ecological impacts. Decisions to retain or remove these aging dams occur within a complex context of both ecological and social considerations. Historically, stream connectivity restoration planning has focused on biophysical criteria. However, aquatic barriers are embedded in social contexts which constrain restoration decisions in the Hudson Valley and beyond. Over the life of the program, Hudson River Estuary Program staff have found considerable challenges in implementing connectivity restoration efforts due to social and institutional obstacles. Furthermore, existing dam removal efforts are often limited by low available information around the social feasibility of dam removal. Data on the recreational, aesthetic, and cultural importance of a given dam can provide important context for resource managers, advocacy groups, and communities. This project aims to satisfy these information gaps through quantification of social attributes using publicly available GIS data in New York State. By compiling these data for both inventoried dams and for ‘ghost’ dams detected via machine learning, this work expands the scope and breadth of social data available. Comprehensive assessments of the social importance of dams will help resource managers and local NGOs with opportunistic removals, while driving restoration efforts towards realistic suggestions for future removals.