Everyday Online Sharing

People make a range of everyday decisions about how and whether to share content withdi erent people, across di erent platforms and services, during a variety of tasks. Thesesharing decisions can encompass complex preferences and a variety of access-control di-mensions. In this thesis I examine potential methods for improving sharing mechanisms bybetter understanding the everyday online sharing environment and evaluating a potentialsharing tool.I first present two studies that explore how current sharing mechanisms may fallshort on social networking sites, leading to suboptimal outcomes such as regret or selfcensorship. I discuss the implications of these suboptimal outcomes for the design ofbehavioral nudging tools and the potential for improving the design of selective-sharingmechanisms. I then draw on a third study to explore the broader “ecosystem” of availablechannels created by the services and platforms people move between and combine toshare content in everyday contexts. I examine the role of selective-sharing features in thebroader audience-driven and task-driven dynamics that drive sharing decisions in thisenvironment. I discuss the implications of channel choice and dynamics for the design ofselective-sharing mechanisms.Using insights from current shortfalls and ecosystem-level dynamics I then presenta fourth study examining the potential for adding topic-driven sharing mechanisms toFacebook. I use design mockups and a lab-based interview to explore participants’ hypo-thetical use cases for such mechanisms. I find that these mechanisms could potentially beuseful in a variety of situations, but successful implementation would require accountingfor privacy requirements and users’ sharing strategies.