CAREER: Banalytics: Behavioral Network Analytics with Data Transparency

职业：Banalytics：具有数据透明度的行为网络分析

• 批准号: 1254035
• 负责人: Augustin Chaintreau
• 金额: $ 50万
• 依托单位: Columbia University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-04-15 至 2019-03-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1254035&HistoricalAwards=false
• 关键词: CAREER; Banalytics; Behavioral; Network; Analytics

Data from customers become central to many companies' business, and tomorrow's society's progress critically depends on scientists and public decision makers accessing citizens' data. But how to reconcile progress with privacy? This dilemma, everyday, is getting worse, because we lack an abstraction where analytics -- the science of identifying and exploiting individual types and trends -- are transparent to users and they can effectively own and trade their data. Today's analytics on proprietary data, and its highly debated need for regulation, seems a necessary evil for a lack of credible alternative. This project aims at unlocking this tussle by (1) building behavioral analytics that are compatible with distributed systems of personal data, (2) showing how context and social influence can be better leveraged, and (3) enabling incremental deployment along mutual benefits to make privacy economically efficient. The principal investigator will explore a new abstraction -- Behavioral Networks -- and show its tractability using recent results in matrix factorization, algorithms exploiting social influence, and analysis of networked incentives. Banalytics will demonstrate its applicability to various analytics tasks, including data collection, behavioral targeting, content rating and recommendation. Broader Impact:The need to regulate proprietary access to personal data is heavily discussed towards a new Privacy Bill. Unfortunately, controlling personal data used behind closed doors is highly complex, making enforcement of top-down regulation either ineffective or potentially disastrous for the free and thriving life of the web. The Banalytics project explores and makes available alternative designs empowering users, to inform this important societal debate towards better self-regulation.Not only are sound solutions to reconcile privacy and progress essential, but they need to be disseminated and understood broadly. Banalytics aims to impact the education of students at large -- not only future engineers but also the future journalists informing our citizens -- on the management of personal information and its technical, economic and societal aspects. Through close collaboration with the Columbia School of Journalism, the principal investigator will promote a unique interdisciplinary education program to allow all students and citizens, especially those who might not otherwise express interest in computer science, to be engaged in this effort.

来自客户的数据成为许多公司业务的核心，未来社会的进步严重依赖于科学家和公共决策者对公民数据的访问。但如何协调进步与隐私？这种困境每天都在变得更糟，因为我们缺乏一种抽象，在这种抽象中，分析——识别和利用个人类型和趋势的科学——对用户是透明的，他们可以有效地拥有和交易他们的数据。如今对专有数据的分析，以及对其进行监管的必要性备受争议，似乎是由于缺乏可靠的替代方案而造成的必然之害。该项目旨在通过(1)建立与个人数据分布式系统兼容的行为分析，(2)展示如何更好地利用环境和社会影响，以及(3)实现互利的增量部署，使隐私在经济上有效。首席研究员将探索一种新的抽象概念——行为网络，并使用矩阵分解、利用社会影响的算法和网络激励分析的最新结果来展示其可追溯性。Banalytics将展示其对各种分析任务的适用性，包括数据收集、行为定位、内容评级和推荐。更广泛的影响：在新的隐私法案中，对个人数据的专有访问进行规范的必要性进行了大量讨论。不幸的是，控制秘密使用的个人数据是非常复杂的，这使得自上而下的监管要么无效，要么对自由繁荣的网络生活造成潜在的灾难性影响。Banalytics项目探索并提供了授权用户的替代设计，以告知这一重要的社会辩论，以更好地进行自我监管。调和隐私和进步的合理解决方案不仅至关重要，而且需要广泛传播和理解。分析旨在影响广大学生的教育-不仅是未来的工程师，而且是未来的记者告知我们的公民-在个人信息及其技术，经济和社会方面的管理。通过与哥伦比亚大学新闻学院的密切合作，首席研究员将推动一项独特的跨学科教育计划，让所有学生和公民，特别是那些可能对计算机科学不感兴趣的人，参与到这项努力中来。