SciSIP: Knowledge Networks and the Dynamics of Innovation

SciSIP：知识网络和创新动力

• 批准号: 1360058
• 负责人: Kristina Lerman
• 金额: $ 18万
• 依托单位: University of Southern California
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2014
• 资助国家: 美国
• 起止时间: 2014-09-01 至 2017-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1360058&HistoricalAwards=false
• 关键词: SciSIP; Knowledge; Networks; Dynamics; Innovation

The central tenet of this project is that knowledge discovery and valuation is a human activity, and as such, it is subject to cognitive heuristics and biases, or mental shortcuts that help people make quick decisions. Social and economic progress is driven by scientific discoveries, and technological and legal innovations. However, as new knowledge accumulates at an accelerating pace through the publication of new scientific papers, patent applications and legal opinions, it becomes ever more difficult to identify information that is critical for innovation. In order to create tools to speed up innovation, we first need to understand how people find and evaluate knowledge. This project will analyze patterns of citation networks in three domains -- physics papers, patents and federal court decisions -- to learn how scholars and innovators discover and evaluate knowledge.Behavioral data for studying cognitive heuristics is available in the form of citation networks. These networks capture the decisions that scholars and innovators made about what relevant documents to reference in their own work. By conducting comparative empirical analysis of citations made by physics papers, patents, and federal court decisions, this project will identify the strategies people use to decide what information to attend to, especially under conditions of information overload, and study the interplay between these strategies, the quality of information, and the decisions of others. In addition to its contributions to understanding how ideas are discovered and evaluated, this project will make a novel, clean data set of legal citations publicly available. The insights produced by this research will lead to new, robust measures of information quality and impact. The new understanding of the role of cognitive heuristics in citation will inform the design of next generation knowledge discovery tools that will help people to more optimally leverage citations to improve the efficiency and robustness of discovery and innovation.

这个项目的中心原则是，知识发现和评估是一项人类活动，因此，它受制于认知启发式和偏见，或帮助人们快速做出决定的心理捷径。社会和经济进步是由科学发现、技术和法律创新推动的。然而，随着新的科学论文、专利申请和法律意见的发表，新知识的积累速度越来越快，识别对创新至关重要的信息变得越来越困难。为了创造加速创新的工具，我们首先需要了解人们是如何发现和评估知识的。这个项目将分析三个领域的引文网络模式--物理论文、专利和联邦法院裁决--以了解学者和创新者如何发现和评估知识。研究认知启发式的行为数据以引文网络的形式提供。这些网络记录了学者和创新者关于在他们的工作中参考哪些相关文件的决定。通过对物理论文、专利和联邦法院裁决的引用进行比较实证分析，这个项目将确定人们用来决定关注哪些信息的策略，特别是在信息过载的情况下，并研究这些策略、信息质量和其他人的决定之间的相互作用。除了有助于理解想法是如何被发现和评估的，这个项目还将提供一个新颖、干净的法律引用数据集供公众使用。这项研究产生的见解将导致对信息质量和影响的新的、强有力的衡量标准。对认知启发式在引文中作用的新理解将指导下一代知识发现工具的设计，这些工具将帮助人们更优化地利用引文来提高发现和创新的效率和稳健性。