Abstract-Alcohol consumption is the number one risk factor for morbidity and mortality among young people. In late adolescence and early adulthood, excessive drinking and intoxication are more common than in any other life period, increasing the risk of adverse physical and psychological health consequences. In this paper, we examine the feasibility of using smartphone sensor data and machine learning to automatically characterize and classify drinking behavior of young adults in an urban, ecologically valid nightlife setting. Our work has two contributions. First, we use previously unexplored data from a large-scale mobile crowdsensing study involving 241 young participants in two urban areas in a European country, which includes phone data (location. accelerometer, Wifi, Bluetooth, battery, screen, and app usage) along with self-reported, fine-grain data on individual alcoholic drinks consumed on Friday and Saturday nights over a three-month period. Second, we build a machine learning methodology to infer whether an individual consumed alcohol on a given weekend night, based on her/his smartphone data contributed between 8PM and 4AM. We found that accelerometer data is the most informative single cue, and that a combination of features results in an overall accuracy of 76.6%.

This article explores youth drinking in Zurich, Switzerland, on both public squares away from nightlife areas, referred to as 'square street drinking' and on the street within the vicinity of nightclubs, defined as 'club street drinking'. Taking a relational space approach, the analysis adds a social perspective to the dominant economic-political perspective to drinking in urban nightlife zones. The results suggest that the normative landscapes of drinking are constructed differently: the same regulation by police and social workers works differently between the two areas both in terms of inclusion and exclusion as well as in terms of how the material and social dimensions interact. Production and regulation are dependent on how young people participate in these processes. This finding suggests that it would be fruitful to develop a regulation approach on drinking in the post-industrial city that is sensitive to young people as co-producers of space. AbstractThis article explores youth drinking in Zurich, Switzerland, on both public squares away from nightlife areas, referred to as 'square street drinking' and on the street within the vicinity of nightclubs, defined as 'club street drinking'. Taking a relational space approach, the analysis adds a social perspective to the dominant economicpolitical perspective to drinking in urban nightlife zones. The results suggest that the normative landscapes of drinking are constructed differently: the same regulation by police and social workers works differently between the two areas both in terms of inclusion and exclusion as well as in terms of how the material and social dimensions interact. Production and regulation are dependent on how young people participate in these processes. This finding suggests that it would be fruitful to develop a regulation approach on drinking in the post-industrial city that is sensitive to young people as co-producers of space.

In the last few decades, an engaged and sophisticated discussion about the production of data and power relations has developed within feminist methodology. Positionality, i.e. the set of relations constituting informants' and researchers' subject positions, has been widely used as an analytical tool to account for the complicated ways in which data are co-constructed in fieldwork. Based on our own experience of fieldwork conducted in the city of Zurich, however, we argue that sexuality is underrepresented in this debate. First, reflexive writing on fieldwork has been reluctant to consider sexuality as a category in the same way, for instance, as gender or race. Second, even apparently innocuous sexualisations have a considerable effect on the constitution of data and are therefore worth including in the analysis. In this article, we examine how flirtation as a part of the participant -researcher relation has re-shaped the research encounters in our respective research projects. We discuss the complex navigations between conflicting rationales that it entailed for us as researchers, depict the minor and major shifts in positionalities that emerge from the flirtation and examine the reasons why we sometimes embraced flirtation and sometimes rejected it. The objective of the article is to further enrich feminist methodological writing, and to suggest to the reader the potential for including various shades of sexual performances, such as apparently harmless flirtation, into our reflections on data collection.

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We present a mobile crowdsourcing study to capture and examine the nightlife patterns of two youth populations in Switzerland. Our contributions are three fold. First, we developed a smartphone application to capture data on places, social context and nightlife activities, and to record mobile videos capturing the ambiance of places. Second, we conducted an "in-the-wild" study with more than 200 participants over a period of three months in two Swiss cities, resulting in a total of 1,394 unique place visits and 843 videos that spread across place categories (including personal homes and public parks), social and ambiance variables. Finally, we investigated the use of automatic ambiance features to estimate the loudness and brightness of places at scale, and found that while features are reliable with respect to video content, videos do not always reflect the place ambiance reported by people in-situ. We believe that the developed methodology provides an opportunity to understand the physical mobility, activities, and social context of youth as they experience different aspects of nightlife.