Abstract
While social sciences and humanities are increasingly including computational methods in their research, anthropology seems to be lagging behind. But it does not have to be so. Anthropology is able to merge quantitative and qualitative methods successfully, especially when traversing between the two. In the following contribution, we propose a new methodological approach and describe how to engage quantitative methods and data analysis to support ethnographic research. We showcase this methodology with the analysis of sensor data from a University of Ljubljana’s faculty building, where we observed human practices and behaviours of employees during working hours and analysed how they interact with the building and their environment. We applied the proposed circular mixed methods approach that combines data analysis (quantitative approach) with ethnography (qualitative approach) on an example of a “smart building” and empirically identified the main benefits of the new anthropological methodology.
Highlights
Social sciences and humanities are rapidly adopting computational approaches and software tools, resulting in an emerging field of digital humanities (Klein and Gold 2016) and computational social sciences (Conte et al 2012)
With an increasing availability of data coming from social networks and wearable devices among other sources (Miller et al 2016; Gershenfeld and Vasseur 2014), anthropologists can easier than ever dive into data analysis and study humans and their societies, subcultures and cultures quantitatively as well as qualitatively
The main purpose of our study was to demonstrate how anthropologists can use statistics and data visualisation to establish the essential facts of the observed phenomena and how the traditional anthropological methods, which have not significantly changed since the early 20th century, when Malinowski (2002 [1922]) carried out his ground-breaking ethnographic research at the Trobriand Islands, can be complemented and upgraded by data analysis
Summary
Social sciences and humanities are rapidly adopting computational approaches and software tools, resulting in an emerging field of digital humanities (Klein and Gold 2016) and computational social sciences (Conte et al 2012). With an increasing availability of data coming from social networks and wearable devices among other sources (Miller et al 2016; Gershenfeld and Vasseur 2014), anthropologists can easier than ever dive into data analysis and study humans and their societies, subcultures and cultures quantitatively as well as qualitatively. With this contribution, we tentatively place anthropology in the field of digital humanities, mostly because the suggested approach is multidisciplinary and by analogy similar to the shifts between distant and close reading ( Jänicke et al 2015) in literary studies. Just like distant reading needs close reading to understand the style, themes, and subtle meanings of a literary work, so does data analysis need an ethnographic approach to contextualize the information and extract subtle meanings of individual human experience
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