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.

该项目的目标是解决人们对社交媒体中个人信息共享的隐私风险的担忧。 低社会经济地位和代表性不足的人群报告说，他们特别担心自己在社交媒体上的数字隐私。 该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使新的机器学习方法能够检测自我披露的个人信息，社交网络和同伴对隐私相关行为的影响，以及特定人群的隐私风险。该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，以了解不同社会经济群体的自我披露态度和行为的差异。为此，该项目正在开发和整合社交媒体自我相关共享行为的新措施，包括受众，披露敏感性，直接与间接披露，群体隐私以及平台和社区规范。研究团队是：对个人信息披露进行小数据和大数据实证研究，开发基于数据的规范信息流描述和衡量背景完整性的指标，并正在试验原型技术，以实现隐私管理的公平性。 该项目以参与性设计和治理的核心原则为基础。这些原则通过广泛的社区外展和相互学习的嵌入式过程来实施，包括实地研究，社区研讨会和合作原型设计。该奖项反映了NSF的法定使命，并被认为值得通过使用基金会的知识价值和更广泛的影响审查标准进行评估来支持。