The purpose of this study is to share the development of a new analytical tool, the Paleontological Identity Taxonomy (PIT), for characterizing members of a science community of practice that is sensitive to and descriptive of individual differences, but also inclusive of a broad range of people who identify with the domain, from those that are strictly interest-based to those with professional credentials. Via the use of embedded mixed methods, including aggregating social network data and iterative coding sessions, we present the PIT as a valid and reliable tool which can be used to characterize members of digital social spaces, an issue previously viewed as a limitation for use of social network analysis in social science research. We conclude with remarks concerning the design of effective scientific learning and communication for social media, including how to recognize and support the diversity of community members’ expertise.