Lia Emanuel

Who am I? Representing the self offline and in different online contexts

Influence of four offline and online contexts on self-disclosure is examined.Individuals disclose the more information offline than any online context.Type of online space influenced the amount and type of information disclosed.Contextual factors appeared more influential in disclosure than personality factors. The present paper examines the extent to which self-presentation may be affected by the context in which is it undertaken. Individuals were asked to complete the Twenty Statements Test both privately and publicly, but were given an opportunity to withhold any of their personal information before it was made public. Four contexts were examined: an offline context (face-to-face), an un-contextualized general online context, or two specific online contexts (dating or job-seeking). The results suggested that participants were willing to disclose substantially less personal information online than offline. Moreover, disclosure decreased as the online context became more specific, and those in the job-seeking context disclosed the least amount of information. Surprisingly, individual differences in personality did not predict disclosure behavior. Instead, the results are set in the context of audience visibility and social norms, and implications for self-presentation in digital contexts are discussed.

What does your profile really say about you?: privacy warning systems and self-disclosure in online social network spaces

This paper reports current progress on the design and initial evaluation of an innovative privacy feedback system aimed to provide social network users with tailor-made feedback about their identity exposure online. Preliminary results suggest our feedback system, based on a research driven model of identity, appears to reduce the amount of information individuals disclose about themselves in social network spaces. We discuss the impact of our feedback system on the way individuals share information online, as well as suggestions for a more fine-grained evaluation and future development of this feedback system.

Innovations in autonomous systems: Challenges and opportunities for human-agent collaboration

Autonomous agents are rapidly becoming collaborative partners in addressing diverse industry and social problem domains. With this shift brings a number of challenges and opportunities in understanding and designing for the dynamics involved in human and agents working collectively. This session will facilitate a wider discussion on the current socio-technical challenges for collaborative agent systems and human-agent interaction across a range of disciplines, and how we move forward to meet those challenges.

Pathways to identity: using visualization to aid law enforcement in identification tasks

The nature of identity has changed dramatically in recent years and has grown in complexity. Identities are defined in multiple domains: biological and psychological elements strongly contribute, but biographical and cyber elements also are necessary to complete the picture. Law enforcement is beginning to adjust to these changes, recognizing identity’s importance in criminal justice. The SuperIdentity project seeks to aid law enforcement officials in their identification tasks through research of techniques for discovering identity traits, generation of statistical models of identity and analysis of identity traits through visualization. We present use cases compiled through user interviews in multiple fields, including law enforcement, and describe the modeling and visualization tools design to aid in those use cases.

Utility evaluation of models

In this paper, we present three case studies of utility evaluations of underlying models in software systems: a user-model, technical and social models both singly and in combination, and a research-based model for user identification. Each of the three cases used a different approach to evaluating the model and each had challenges to overcome in designing and implementing the evaluation. We describe the methods we used and challenges faced in designing the evaluation procedures, summarize the lessons learned, enumerate considerations for those undertaking such evaluations, and present directions for future work.