Presentation of self (via Goffman) is becoming increasingly popular as a means for explaining differences in meaning and activity of online participation. This article argues that self-presentation can be split into performances, which take place in synchronous “situations,” and artifacts, which take place in asynchronous “exhibitions.” Goffman’s dramaturgical approach (including the notions of front and back stage) focuses on situations. Social media, on the other hand, frequently employs exhibitions, such as lists of status updates and sets of photos, alongside situational activities, such as chatting. A key difference in exhibitions is the virtual “curator” that manages and redistributes this digital content. This article introduces the exhibitional approach and the curator and suggests ways in which this approach can extend present work concerning online presentation of self. It introduces a theory of “lowest common denominator” culture employing the exhibitional approach.

We describe an interview-based data-collection procedure for social network analysis designed to aid gathering information about the people known by a respondent and reduce problems with data integrity and respondent burden. This procedure, a participant-aided network diagram (sociogram), is an extension of traditional name generators. Although such a diagram can be produced through computer-assisted programs for interviewing (CAPIs) and low technology (i.e., paper), we demonstrate both practical and methodological reasons for keeping high technology in the lab and low technology in the field. We provide some general heuristics that can reduce the time needed to complete a name generator. We present findings from our Connected Lives field study to illustrate this procedure and compare to an alternative method for gathering network data.

This paper presents a data collection effort designed to incorporate the social dimension in social activity-travel behavior by explicitly studying the link between individuals' social activities and their social networks. The main hypothesis of the data collection effort is that individuals' travel behavior is conditional upon their social networks; that is, a key cause of travel behavior is the social dimension represented by social networks. With this hypothesis in mind, and using survey and interview instruments, the respondents' social networks are collected using an egocentric approach that is constituted by the interplay between their individual social structures and their social activity behavior. More explicitly, individuals' networks are a context within which to elicit social activity-travel generation, spatial distribution, and information communication and technology use. The resultant dataset links aspects, in novel ways, that have been rarely studied together, and provides a sound base of theory and method to study and potentially give new insights about social activity-travel behavior.

How predictable are life trajectories? We investigated this question with a scientific mass collaboration using the common task method; 160 teams built predictive models for six life outcomes using data from the Fragile Families and Child Wellbeing Study, a high-quality birth cohort study. Despite using a rich dataset and applying machine-learning methods optimized for prediction, the best predictions were not very accurate and were only slightly better than those from a simple benchmark model. Within each outcome, prediction error was strongly associated with the family being predicted and weakly associated with the technique used to generate the prediction. Overall, these results suggest practical limits to the predictability of life outcomes in some settings and illustrate the value of mass collaborations in the social sciences.

Geographies of codified knowledge have always been characterized by stark core-periphery patterns: with some parts of the world at the center of global voice and representation, and many others invisible or unheard. However, many have pointed to the potential for radical change as digital divides are bridged and 2.5 billion people are now online. With a focus on Wikipedia, which is one of the world's most visible, most used, and most powerful repositories of user-generated content, we investigate whether we are now seeing fundamentally different patterns of knowledge production. Even though Wikipedia consists of a massive cloud of geographic information about millions of events and places around the globe put together by millions of hours of human labor, it remains that the encyclopedia is characterized by uneven and clustered geographies: there is simply not a lot of content about much of the world. The paper then moves to describe the factors that explain these patterns, showing that while just a few conditions can explain much of the variance in geographies of information some parts of the world remain well below their expected values. These findings indicate that better connectivity is only a necessary, but not a sufficient condition for the presence of volunteered geographic information about a place. We conclude by discussing the remaining social, economic, political, regulatory, and infrastructural barriers that continue to disadvantage many of the world's informational peripheries. The paper ultimately shows that, despite many hopes that a democratization of connectivity will spur a concomitant democratization of information production, internet connectivity is not a panacea, and can only ever be one part of a broader strategy to deepen the informational layers of places.

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