New sources of ‘big data’ are regularly described as revolutionizing the study of urban life. Of particular interest is analyzing gentrification, which has proven a challenging endeavor with conventional methods. Big data may offer a new approach to the persistent problem of defining and measuring gentrification, while also allowing us to rethink broader questions about theory and methodology in urban geography. Using geotagged Twitter data, we demonstrate how the changing geographies of users’ tweets are proxies for the evolving social and spatial contours of urban neighborhoods. We use the case of Lexington, Kentucky to analyze the mobilities and relational connections of neighborhood residents and visitors as gentrification intensified over time. We argue that these kinds of big data allow for an analytical approach that focuses on the dynamic, relational connections between people and places, and provides a useful, additional avenue in understanding a process as complex and multifaceted as gentrification.