CAREER: Social and Economic Consequences of Information Diffusion in Networks

该项目是一个三管齐下的研究和教育计划，重点关注网络中的信息——它的分布、扩散、价值以及对社会和经济结果的影响。首先，该项目将绘制真实组织中信息随时间的流动图，并将生产的经济理论与社会网络理论相结合，以估计信息扩散对个人和团队生产力的影响。本研究将推动有关信息工作者生产与生产力的经济学理论的发展；社会网络中信息运动的社会学理论在保护隐私的同时分析数字网络中的信息内容的技术方法并采用统计方法确定网络结构与生产力之间的因果关系。其次，研究将利用在线社交网络上的数据来确定对产品采用和需求的同伴影响的估计，并将开发和应用新的统计技术来分离选择、同质性和混淆因素的影响，以优化有针对性的点对点信息传播。第三，本研究将开发一类基于网络的行为变化在社会网络中的扩散模型，并使用来自五个大规模网络数据集的社会关系和健康相关行为的经验数据对这些模型进行参数化和验证。该项目的中心目标是：1)估计和提高信息工作者的生产力，2)模拟、衡量和改进点对点病毒式营销和需求估计，以及3)改进与健康有关的预防和干预战略。拟议的活动旨在对科学、教育和社会产生更广泛的影响。我们对信息工作者生产力的理解是我们未来经济增长的基石，从而是我们繁荣和福利的基石。该项目还旨在改进针对疾病预防、肥胖和吸毒等行为和结果的干预和预防策略。制定可靠的、可扩展的统计方法，确定疾病、肥胖、吸烟和犯罪扩散的因果关系，可以改变社会政策，确保卫生干预措施有适当的针对性。发展处理大型动态网络数据集的技术基础设施、保护隐私的文本分析和估计网络中信息扩散影响的统计方法，对电信、流行病学、医学、社会政策以及任何以网络外部性和局部网络效应为特征的行业或社会领域都有影响。在教育方面，该项目将利用课堂上的研究计划来强调网络和信息对商业战略、社会和健康的重要性。研讨会将围绕网络中信息扩散的相关主题，在学术界和工业界之间建立一个新的合作研究社区。

This project is a three-pronged program of research and education focused on information in networks - its distribution, diffusion, value, and consequences for social and economic outcomes. First, this project will map the flow of information in real organizations over time and will combine economic theories of production with social network theory to estimate the effects of information diffusion on the productivity of individuals and teams. This work will advance economic theory concerning information worker production and productivity; sociological theory concerning the movement of information in social networks; technical methods for analyzing information content in digital networks while preserving privacy; and statistical methods to identify causal relationships between network structure and productivity. Second, the research will utilize data on online social networks to identify estimates of peer influence in product adoption and demand, and it will develop and apply new statistical techniques to separate influence from selection, homophily and confounding factors to optimize targeted peer-to-peer information diffusion. Third, the research will develop a general class of network-based models of the diffusion of behavior change in social networks, and parameterize and validate these models using empirical data on social relationships and health related behaviors from five massive networked datasets.The central goals of the project are: 1) to estimate and enhance the productivity of information workers, 2) to model, measure and improve peer-to-peer viral marketing and demand estimation, and 3) to improve health-related prevention and intervention strategies. The proposed activities are designed to have broader impact for science, education and society. Our understanding of information worker productivity is a cornerstone of our future economic growth and thus our prosperity and welfare. The project also aims to improve intervention and prevention strategies for behaviors and outcomes such as disease prevention, obesity, and drug use. Developing reliable, scalable statistical methods for establishing causality in the diffusion of disease, obesity, smoking and delinquency can change social policy to ensure health interventions are appropriately targeted. Development of technical infrastructures to deal with large dynamic networked datasets, privacy preserving text analysis, and statistical methods for estimating the impacts of information diffusion in networks have implications for telecommunications, epidemiology, medicine, social policy and any industry or social sphere characterized by network externalities and local network effects. Educationally, the project will utilize the research program in classes to highlight the importance of networks and information for business strategy, society and health. Workshops will develop a new collaborative research community across academia and industry around topics related to information diffusion in networks.