(Georgia Institute of Technology, 2009-07-06)
Goecks, Jeremy
A social navigation system collects data from its users--its community--about what they are doing, their opinions, and their decisions, aggregates this data, and provides the aggregated data--community data--back to individuals so that they can use it to guide behavior and decisions. In this thesis, I document my investigation of the user experience for social navigation systems that employ activity data. I make three contributions in this thesis. First, I synthesize social navigation systems research with research in social influence, advice-taking, and informational cascades to construct hypotheses about the social navigation user experience. These hypotheses posit that community data from a social navigation system exerts informational influence on users, that users egocentrically discount community data, that herding in social navigation systems can be characterized as informational cascades, and that the size and unanimity of the community data correspond to the strength of the community data's influence. The second contribution of this thesis is an experiment that evaluates the hypotheses about the social navigation user experience; this experiment investigated how a social navigation system can support online charitable giving decisions. The experiment's results support the majority of the hypotheses about the social navigation user experience and provide mixed evidence for the other hypotheses. The implications that arise from the experiment's findings compromise the final contribution of this thesis. These implications concern improving the design of social navigation systems and developing a general framework for evaluating the social influence of social navigation systems.
(Georgia Institute of Technology, 2008-05-19)
Voida, Stephen
The venerable desktop metaphor is beginning to show signs of strain in supporting modern knowledge work. Traditional desktop systems were not designed to support the sheer number of simultaneous windows, information resources, and collaborative contexts that have become commonplace in contemporary knowledge work. Even though the desktop has been slow to evolve, knowledge workers still consistently manage multiple tasks, collaborate effectively among colleagues or clients, and manipulate information most relevant to their current task by leveraging the spatial organization of their work area. The potential exists for desktop workspaces to better support these knowledge work practices by leveraging the unifying construct of activity. Semantically-meaningful activities, conceptualized as a collection of tools (applications, documents, and other resources) within a social and organizational context, offer an alternative orientation for the desktop experience that more closely corresponds to knowledge workers' objectives and goals.
In this research, I unpack some of the foundational assumptions of desktop interface design and propose an activity-centered model for organizing the desktop interface based on empirical observations of real-world knowledge work practice, theoretical understandings of cognition and activity, and my own experiences in developing two prototype systems for extending the desktop to support knowledge work. I formalize this analysis in a series of key challenges for the research and development of activity-based systems. In response to these challenges, I present the design and implementation of a third research prototype, the Giornata system, that emphasizes activity as a primary organizing principle in GUI-based interaction, information organization, and collaboration. I conclude with two evaluations of the system. First, I present findings from a longitudinal deployment of the system among a small group of representative knowledge workers; this deployment constitutes one of the first studies of how activity-based systems are adopted and appropriated in a real-world context. Second, I provide an assessment of the technologies that enable and those that pose barriers to the development of activity-based computing systems.