EAGER: Collaborative Research: Information Diffusion and Opinion Formation in Networked Systems

EAGER：协作研究：网络系统中的信息传播和意见形成

• 批准号: 1137519
• 负责人: Roch Guerin
• 金额: $ 24.75万
• 依托单位: University of Pennsylvania
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2011
• 资助国家: 美国
• 起止时间: 2011-09-01 至 2013-08-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1137519&HistoricalAwards=false
• 关键词: EAGER; Collaborative; Research; Information; Diffusion

Fueled by the ubiquity of communications access, networked systems have become pervasive and given rise to behaviors whose evolution depends on both individual decisions and the interactions on the network. Examples of such behaviors include media sharing websites, where user recommendations influence product adoption decisions of other users, or more generally public discussion forums where past voting records of users provide indications on how they may influence each other and, therefore, how initial opinions may determine the outcome of future votes. Understanding the evolution of decisions in such connected settings can, therefore, be of significant social and economic benefit. For example, this can help predict the adoption of new social policies, or more pragmatically the commercial success of a new shared application. The importance of those questions has attracted much recent attention, but due to the complexity of networked interactions, much remains to be done. This project takes a multi-disciplinary approach to tackling these challenging questions, and seeks to build on models from statistical physics developed to capture the interactions of charged particles, which interact with each other in a manner akin to how users influence each other in a social network. If successful, the work can both expand the set of tools available to explore the behavior of networked systems, and offer insight into specific problems of interest.This project explores two fundamental aspects of networked systems, namely, the formation of opinions in networks, and how adoption decisions are made when they are influenced by network neighbors. Networked systems can be of many different forms, including communication networks, social networks, political networks, geographical networks, etc., and are characterized by the fact that connections between network members influence their interactions. Characterizing these interactions is a complex task. The two main goals of the project are to (i) extend models from statistical physics to apply them to fundamental problems in networked systems; and (ii) empirically validate the predictive abilities of these models. Specifically, the project seeks to leverage and extend the Ising spin glass model, and apply these extensions to problems of opinion formation and adoption decisions in networked systems. Empirical validation of the results will then be sought through comparison to data collected from social media websites.

由于通信访问的无处不在，网络系统变得普遍，并引起了行为，其演变取决于单个决策和网络上的交互。 此类行为的示例包括媒体共享网站，用户建议会影响其他用户的产品采用决策，或更普遍的公共讨论论坛，在这些论坛上，过去的投票记录提供了有关它们如何相互影响的指示，因此，初始意见如何确定未来投票的结果。 因此，了解在这种相互联系的环境中决策的演变可能具有重大的社会和经济利益。 例如，这可以有助于预测新的社会政策的采用，或更务实地务实地是新共享应用程序的商业成功。 这些问题的重要性引起了最近的关注，但是由于网络互动的复杂性，还有很多事情要做。 该项目采用多学科的方法来解决这些具有挑战性的问题，并试图建立在开发的统计物理学的模型的基础上，以捕获带电粒子的相互作用，这些粒子以类似于用户在社交网络中相互影响的方式相互作用。 如果成功，这项工作既可以扩展可用的工具来探索网络系统的行为，又可以深入了解特定感兴趣的问题。本项目探讨了网络系统的两个基本方面，即网络中的意见形成，以及在受网络邻居影响时如何做出的采用决策。 网络系统可以具有许多不同的形式，包括通信网络，社交网络，政治网络，地理网络等，其特征是网络成员之间的联系影响了他们的交互。表征这些互动是一项复杂的任务。 该项目的两个主要目标是（i）将模型从统计物理学扩展到将它们应用于网络系统中的基本问题； （ii）从经验上验证这些模型的预测能力。具体而言，该项目旨在利用和扩展Ising旋转玻璃模型，并将这些扩展应用于网络系统中的意见形成和采用决策问题。 然后，将通过与从社交媒体网站收集的数据进行比较来寻求对结果的经验验证。