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.

在通信接入无处不在的推动下，网络系统已经变得普遍，并产生了一些行为，这些行为的演变取决于个人决策和网络上的交互。 此类行为的示例包括媒体共享网站，其中用户推荐影响其他用户的产品采用决策，或更普遍的公共讨论论坛，其中用户过去的投票记录提供了有关他们如何相互影响的指示，以及因此初步意见如何确定未来投票的结果。 因此，了解此类互联环境中决策的演变可以产生重大的社会和经济效益。 例如，这可以帮助预测新社会政策的采用，或者更务实地预测新共享应用程序的商业成功。 这些问题的重要性最近引起了人们的广泛关注，但由于网络交互的复杂性，还有很多工作要做。 该项目采用多学科方法来解决这些具有挑战性的问题，并寻求建立在统计物理学模型的基础上，这些模型是为了捕获带电粒子的相互作用而开发的，带电粒子之间的相互作用类似于用户在社交中相互影响的方式。网络。 如果成功，这项工作既可以扩展可用于探索网络系统行为的工具集，又可以深入了解感兴趣的具体问题。该项目探讨了网络系统的两个基本方面，即网络中意见的形成和当受网络邻居影响时如何做出采用决策。 网络系统可以有多种不同的形式，包括通信网络、社交网络、政治网络、地理网络等，其特点是网络成员之间的联系影响他们的互动。表征这些相互作用是一项复杂的任务。 该项目的两个主要目标是（i）扩展统计物理学的模型，将其应用于网络系统中的基本问题； (ii) 凭经验验证这些模型的预测能力。具体来说，该项目旨在利用和扩展伊辛自旋玻璃模型，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结果的实证验证。