Daniel Lobo is a PhD student in the Department of Sociology at UC Berkeley and a Computational Social Science Fellow at the Berkeley Institute of Data Science. He believes that individuals make choices based on their preferences within a social context. Thus, his sociological project, like those of Émile Durkheim and Pierre Bourdieu, seeks to reveal the social in the apparently most individual forms of behavior. He is interested in how social conditions, both material and symbolic, shape the choices individuals make within our political economy–choices like where to live, who to build relationships with, whether and where to go to school, or where to work. Understanding the complex cognitive interaction between internalized dispositions and objective structures, including digital structures of the 21st century, is core to this research project. Consequently, he draws most heavily on the work of Bourdieu, including his concepts of social reproduction, social fields, cultural and social capital, habitus, and symbolic power. Daniel aims to use the empirical power of computational social science to more precisely and comprehensively measure the effects of these theoretical concepts and others in his work. He holds a BA in Social Studies, with high honors, from Harvard College.
Culture, economic sociology, sociology of education, social theory, race & ethnicity, social psychology, computational social science