Overview: Social media and other social computing platforms let people share more information about themselves and others, with more people than ever before. Even as people enjoy the benefits of information sharing, it has become clear that people have intuitions about the operation of social media platforms that can lead to unanticipated consequences, such as information becoming visible in ways that are problematic for one’s self-presentation. Information about oneself that is shared by others, for example, can spread rapidly to unexpected audiences or contexts. As a result, people have lost their jobs due to inadvertently shared photographs, suffered after being identified by cyberbullies or predators on anonymous social platforms, and been embarrassed by behavior that may be acceptable in some contexts, but not others. It is tempting to blame these negative outcomes on individuals who were careless with privacy settings or who simply shared inappropriate information. There is increasing evidence, however, that the misunderstandings leading to these incidents stem from a fundamental shift in how information related to the presentation of self is generated, disseminated and perceived. What was once a largely interpersonal process, self-presentation now occurs in a complex cyber-human system consisting of people generating content about themselves and others on various media platforms, each with algorithmic mechanisms that govern the visibility of content to various audiences, often in opaque ways. The objectives of this proposal are three-fold: (1) the development of a theoretical and practical framework for the presentation of self that offers a fundamentally new, cyber-human system approach to understanding self-presentation in a networked world, (2) contribute empirically to our understanding of how people conceptualize the operation of visibility mechanisms on social media platforms, and (3) to develop computational models and tools to automatically infer a user’s understanding of visibility mechanisms. We will use cyber-human systems as a lens for understanding self-presentation as it occurs in a complex environment in which the human and computational components described above interact in ways that have difficult-to-predict outcomes. We use this lens to develop and validate theoretical and computational frameworks for understanding self-presentation in a networked world by focusing on how people conceptualize the operation of social media platforms, especially the algorithms that govern the visibility of content. These objectives will be accomplished through a series of novel empirical studies, combined with computational models that infer a user’s conceptualization of a social media platform and that allow users to reflect on their understanding of the platform. Keywords: self-presentation, algorithms, social media, cyberbullying, audience, privacy Intellectual Merit: This work builds on and integrates substantial research in the areas of self presentation and impression management, and the role of platforms and algorithms in people’s online experience. It provides three unique contributions: 1) a framework for understanding self-presentation in networked spaces that takes a cyber-human systems view of behavior and, the platforms and mechanisms that render different content visible to audiences; 2) empirical data from novel surveys and experiments on how people understand and consider the role of algorithms and other visibility mechanisms; and 3) novel computational models to aid in analysis, prediction and r
|Effective start/end date||9/1/16 → 8/31/21|
- National Science Foundation (IIS-1617387)
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint.