SaTC: CORE: Small: Toward Privacy Equity through Contextual Understanding of Self-Disclosure

SaTC：核心：小：通过自我披露的情境理解实现隐私公平

• 批准号: 2247723
• 负责人: Sarah Rajtmajer
• 金额: $ 59.99万
• 依托单位: Pennsylvania State Univ University Park
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-06-01 至 2026-05-31
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2247723&HistoricalAwards=false
• 关键词: SaTC; CORE; Small; Toward; Privacy

The goal of this project is to address concerns about the privacy risks to personal information sharing in social media. Low socioeconomic and underrepresented populations report feeling especially concerned about their digital privacy in social media. The project team is studying how socioeconomic status and group identity influence the challenges of privacy self-management. New datasets collected and labeled through this award enable new machine learning approaches for detection of self-disclosed personal information, social network and peer effects on privacy-relevant behaviors, and population-specific privacy risks. Privacy-enhancing technologies designed and developed during the project will support privacy self-management for social media users. To accomplish the goals of the project, research is being undertaken to understand differences in self-disclosure attitudes and behaviors across socioeconomic groups. To do so, the project is developing and integrating novel measures of social media self-relevant sharing behavior, including audience, sensitivity of disclosure, direct vs. indirect disclosure, group privacy, and platform and community norms. The research team is: conducting small- and big-data empirical studies of personal disclosure, developing data-informed descriptions of normative information flow and metrics for measurement of contextual integrity, and is experimenting with prototype technologies to bring equity to privacy management. The project is based on core principles of participatory design and governance. These principles are operationalized through broad community outreach and embedded processes for mutual learning, including field studies, community workshops, and cooperative prototyping.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

该项目的目的是解决社交媒体中个人信息共享的隐私风险的担忧。 社会经济低下和代表性不足的人群报告说，人们特别关注他们在社交媒体中的数字隐私。 项目团队正在研究社会经济地位和群体身份如何影响隐私自我管理的挑战。 通过该奖项收集和标记的新数据集可实现新的机器学习方法，以检测自我披露的个人信息，社交网络和同伴对与隐私相关行为的影响以及特定于人群的隐私风险。在项目期间设计和开发的隐私增强技术将支持社交媒体用户的隐私自我管理。为了实现该项目的目标，正在进行研究以了解社会经济群体之间自我披露态度和行为的差异。为此，该项目正在制定和整合社交媒体自我相关的共享行为的新颖措施，包括受众，披露的敏感性，直接与间接披露，团体隐私以及平台和社区规范。研究团队是：对个人披露的小型和大数据进行实证研究，开发了对规范信息流和指标的数据信息描述，以衡量上下文完整性，并正在尝试使用原型技术来为隐私管理带来公平的公平性。 该项目基于参与式设计和治理的核心原则。这些原则通过广泛的社区外展和相互学习的嵌入过程进行操作，包括现场研究，社区讲习班和合作原型。该奖项反映了NSF的法定使命，并被认为是值得通过基金会的知识分子优点和更广泛的影响来评估的，以评估值得进行评估。