Foursquare is a location-based social network (LBSN) that allows people to share their location with friends by ‘checking-in’ at a given place using their smartphone. The application can also access the location-based recommendations left by other users. Drawing on original qualitative research with a range of Foursquare users, the article sets out to examine this LBSN and its impact on identity in three ways. Using Schwartz and Halegoua’s ‘spatial self’ as ‘a theoretical framework encapsulating the process of online self-presentation based on the display of offline physical activities’, the article first examines the extent to which users understand check-ins as mediating identity. Second, the article explores whether the act of using Foursquare beyond the sharing of location can similarly be seen as contributing to identity. Last, the article examines what effect location-based recommendations might be having on how users subsequently experience themselves.
As a growing number of social media platforms now include location information from their users, researchers are confronted with new online representations of individuals, social networks, and the places they inhabit. To better understand these representations and their implications, we introduce the concept of the “spatial self”: a theoretical framework encapsulating the process of online self-presentation based on the display of offline physical activities. Building on previous studies in social science, humanities, and computer and information science, we analyze the ways offline experiences are harnessed and performed online. We first provide an encompassing interdisciplinary survey of research that investigates the relationships between location, information technology, and identity performance. Then, we identify and characterize the spatial self as well as examine its occurrences through three case studies of popular social media sites: Instagram, Facebook, and Foursquare. Finally, we offer possible research directions and methodological considerations for the analysis of geocoded social media data.
