Opportunistic Collective Experiences: Identifying Shared Situations and Structuring Shared Activities at Distance
Ryan Louie, Kapil Garg, Jennie Werner, Allison Sun, Darren Gergle, Haoqi Zhang
摘要
Despite many available social technologies for connecting at a distance, we don't always find opportunities to actively engage in shared experiences and activities with friends and loved ones, even though this kind of interaction is associated with increased social closeness. To better support active engagement in shared experiences and activities while also making it convenient to find opportunities for interacting in this way, our work explores the design of Opportunistic Collective Experiences (OCEs), or social experiences powered by computer programs that identify opportune moments when users share situations across distance and structure shared activities in those situations. To support interacting with, programming, and executing OCEs, we developed Cerebro, a computational platform that consists of a mobile app that supports users? social interaction, an API for expressing the situations and activities that make up the interactional opportunity, and an opportunistic execution engine that checks for interactional opportunities and executes them when possible. Through a 20 day deployment study tested with groups of geographically-distributed college alumni (N=21), we found that OCEs promoted opportunities for active engagement; facilitated interactions that were socially connecting by structuring ways to engage in shared experiences and activities; and made actively engaging easier by identifying situations appropriate for interacting and structuring how to engage in activities in these situations. We contribute to CSCW (1) a novel interaction that facilitates engaging in shared experiences and activities at distance during coincidental moments; and (2) the design of systems to interact with, program, and execute these kinds of interactions.
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