In this paper we propose data augmented ethnography as a novel mixed methods approach to combine ethnographic, qualitative, observations with social media data collection and computational analysis. Using two brief studies on online interaction as examples we discuss the benefits and challenges of the combination of these two perspectives. We posit that the observations made in the qualitative phase can be quantified and hypothesized together with the data collected later during the analysis stage. Through our case studies we aim to shed light to the differences apparent on the party level and seek to understand how candidates, based on their parties political standing, differ in terms of interactivity. We ask, what insights does a mixed-method approach combining ethnographic observations to computational social science offer to the study of interactivity and its many pregnant forms? To answer this question, we use a large data set collected from different social media platforms before and during the 2015 Parliament Election in Finland. This data consists of both textual data including all candidate updates and the conversations they elicited, as well as field notes written and collected during ethnographic field work period before the elections.