Sociology in the Era of Big Data: The Ascent of Forensic Social Science

Sociology in the Era of Big Data: The Ascent of Forensic Social Science

By
Daniel McFarland, Kevin Lewis, Amir Goldberg
American Sociologist.
2015

The rise of big data—data that are not only large and massively multivariate but concern a dizzying array of phenomena—represents a watershed moment for the social sciences. These data have created demand for new methods that reduce/simplify the dimensionality of data, identify novel patterns and relations, and predict outcomes, from computational ethnography and computational linguistics to network science, machine learning, and in situ experiments. Such developments have led scholars to begin new lines of social inquiry. Company engineers, computer scientists, and social scientists have all converged on big data, creating the possibility of a vibrant “trading zone” for collaboration. However, strong differences in research frameworks help explain why big data may not be an egalitarian trading zone across fields, but rather—at least in the short term—a moment when engineering colonizes sociology more than vice versa. In the long term, however, we suggest there may be the possibility of a constructive synthesis across paradigms in what we term ‘forensic social science.’