SoCS: A Mathematical Framework for Modeling Behavior of Diverse Groups

SoCS：不同群体行为建模的数学框架

• 批准号: 0968370
• 负责人: Kristina Lerman
• 金额: $ 25万
• 依托单位: University of Southern California
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2010
• 资助国家: 美国
• 起止时间: 2010-08-01 至 2012-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=0968370&HistoricalAwards=false
• 关键词: SoCS; Mathematical; Framework; Modeling; Behavior

The Social Web has become an important medium for social interaction and potentially a powerful new computational tool. As people create and share information online, their collective activity shapes the structure and usefulness of the Social Web and can even be used to address a range of problems from collective decision-making to trend prediction. Understanding how the aggregate activity of many interconnected people evolves is crucial to our ability to transform the Social Web into a platform for social computing.Mathematical modeling is a powerful tool for studying collective human activity. In previous work, the PI and collaborators developed a framework for mathematically modeling emergent behavior of groups of users on the Social Web. This framework allowed the modeler to relate aggregate behavior of a group of users to simple descriptions of their individual behavior. However, it failed to take into account key aspects of the Social Web: user diversity and the extent to which social links indicate a commonality of users' interests.The goal of this project is to develop a methodology for modeling diverse groups of users on the Social Web and to understand how user heterogeneity affects group behavior. Mathematical modeling and analysis will lead to better, more effective Web sites by identifying productive ways to display information to users, as well as techniques for promoting collaboration and enhancing participation. Analysis will also lead to new insights into how to use human activity for computation, and eventually a programming toolkit for social computing.

社交网络已经成为社会互动的重要媒介，并有可能成为一种强大的新型计算工具。当人们在网上创造和分享信息时，他们的集体活动塑造了社交网络的结构和实用性，甚至可以用来解决从集体决策到趋势预测的一系列问题。了解许多相互联系的人的总体活动是如何演变的，这对于我们将社交网络转变为社交计算平台的能力至关重要。数学建模是研究人类集体活动的有力工具。在之前的工作中，PI和合作者开发了一个框架，用于对社交网络上用户群体的紧急行为进行数学建模。这个框架允许建模者将一组用户的总体行为与他们个人行为的简单描述联系起来。然而，它没有考虑到社交网络的关键方面：用户多样性和社交链接表明用户兴趣共性的程度。该项目的目标是开发一种方法，用于对社交网络上不同的用户群体进行建模，并了解用户异质性如何影响群体行为。数学建模和分析将通过确定向用户显示信息的有效方法，以及促进协作和加强参与的技术，从而产生更好、更有效的Web站点。分析还将导致对如何使用人类活动进行计算的新见解，并最终形成用于社会计算的编程工具包。