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There is a saying, 'do not paint the devil on the wall', which is commonly taken to mean that one should, for all intents and purposes, avoid portraying something in an overly negative or exaggerated way. The German origin of the proverb is even more interesting. It says: 'One should not paint the devil on the wall, since he will enter the room anyway'[1]. Rather than referring to a moral virtue (don't be overly pessimistic, don't exaggerate), the original proverb is, in itself, a pessimistic view on the world. In short, you don't need to evoke the devil, since he is already here. Or, perhaps, you don't need to exaggerate, since the world is already exaggerated. This special issue started out as an attempt to pursue this idea: If the world is exaggerated, wouldn't this require us to use exaggerated examples to describe it? ...

[1] Man braucht den Teufel nicht an die Wand zu malen, er kommt auch ohne das herein

The era of 'big data' studies and computational social science has recently given rise to a number of realignments within and beyond the social sciences, where otherwise distinct data formats – digital, numerical, ethnographic, visual, etc. – rub off and emerge from one another in new ways. This article chronicles the collaboration between a team of anthropologists and sociologists, who worked together for one week in an experimental attempt to combine 'big' transactional and 'small' ethnographic data formats. Our collaboration is part of a larger cross-disciplinary project carried out at the Danish Technical University (DTU), where high-resolution transactional data from smartphones allows for recordings of social networks amongst a freshman class (N = 800). With a parallel deployment of ethnographic fieldwork among the DTU students, this research set-up raises a number of questions concerning how to assemble disparate 'data-worlds' and to what epistemological and political effects? To address these questions, a specific social event – a lively student party – was singled out from the broader DTU dataset. Our experimental collaboration used recordings of Bluetooth signals between students' phones to visualize the ebb and flow of social intensities at the DTU party, juxtaposing these with ethnographic field-notes on shifting party atmospheres. Tracing and reflecting on the process of combining heterogeneous data, the article offers a concrete case of how a 'stitching together' of digital and ethnographic data-worlds might take place.

This paper describes the deployment of a large-scale study designed to measure human interactions across a variety of communication channels, with high temporal resolution and spanning multiple years-the Copenhagen Networks Study. Specifically, we collect data on face-to-face interactions, telecommunication, social networks, location, and background information (personality, demographics, health, politics) for a densely connected population of 1 000 individuals, using state-of-the-art smartphones as social sensors. Here we provide an overview of the related work and describe the motivation and research agenda driving the study. Additionally, the paper details the data-types measured, and the technical infrastructure in terms of both backend and phone software, as well as an outline of the deployment procedures. We document the participant privacy procedures and their underlying principles. The paper is concluded with early results from data analysis, illustrating the importance of multi-channel high-resolution approach to data collection.