Working the fields of big data: Using big-data-augmented online ethnography to study candidate–candidate interaction at election time

Abstract

The paper proposes big-data-augmented ethnography as a novel mixed-methods approach to studying political discussions in a hybrid media system. Using such empirical setup, the authors examined candidate–candidate online interaction during election campaigning. Candidate–candidate interaction crossing party boundaries is scarce and occurs in the form of negative campaigning via social media, with the shaming of rival candidates and engaging in battles with them. The authors posit that ethnographic observations can be used to contextualize the computational analysis of large data sets, while computational analysis can be applied to validate and generalize the findings made through ethnography.