III-CXT: Computer Science Research Using the Cornell Web Lab to Study Social and Informational Processes on the Web

III-CXT：使用康奈尔大学网络实验室研究网络上的社会和信息过程的计算机科学研究

• 批准号: 0705774
• 负责人: William Arms
• 金额: $ 89.77万
• 依托单位: Cornell University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2007
• 资助国家: 美国
• 起止时间: 2007-10-01 至 2011-09-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0705774&HistoricalAwards=false
• 关键词: III; CXT; Computer; Science; Research

IIS - 0705774Arms, William Y.Cornel UniversityIII-CXT-Computer Science Research Using the Cornell Web Lab to Study Social andInformation Processes on the WebThe project is a collaborative effort between computer scientists and social scientists to advance understanding of the dynamics of the World Wide Web and its impact on science and society. The Web Lab enables social science scholars and others to study issues related to the diffusion of innovation - how new ideas arise and spread across large populations. The proposal addresses fundamental new computing and information science research questions and extends the Web Lab datasets to new levels of depth and complexity so that critical issues of scale can be explored. The project has four goals: (1) to develop large-scale datasets that support wide ranging research about the nature and evolution of the Web, (2) to study human interaction on the Web by combing methods of hypothesis-driven research from the social sciences with large-scale modeling of information structures from computer and information sciences, (3) to understand better how the Web evolves over time by developing models of the creation, modification, and destruction of pages and link structures, and by testing those models on Web-scale snapshots, and (4) to make the datasets available over the TeraGrid.

康奈尔大学计算机科学研究使用康奈尔网络实验室研究网络上的社会和信息过程该项目是计算机科学家和社会科学家之间的合作努力，以促进对万维网的动态及其对科学和社会的影响的理解。网络实验室使社会科学学者和其他人能够研究与创新扩散有关的问题--新想法是如何产生并在大量人口中传播的。该提案解决了基本的新的计算和信息科学研究问题，并将网络实验室的数据集扩展到新的深度和复杂性水平，以便能够探索规模的关键问题。该项目有四个目标：(1)开发支持关于Web的性质和演变的广泛研究的大规模数据集；(2)通过将社会科学的假设驱动研究方法与计算机和信息科学的信息结构大规模建模相结合来研究Web上的人类交互；(3)通过开发页面和链接结构的创建、修改和破坏的模型，并通过在Web规模的快照上测试这些模型，更好地了解Web是如何随着时间的推移演变的，以及(4)通过TeraGrid提供数据集。