Doctoral Dissertation Research: Examining Network Effects on the Spread of Rumor and Misinformation

本项目研究了网络拓扑对谣言传播的影响，并做出了三个主要的智力贡献。首先，它为解释网络与谣言传播之间的关系提供了理论框架。其次，本文对谣言的网络传播进行了实证研究，并与有效信息的传播进行了比较。最后，本项目对社会传染网络模型的主要理论研究产生的假设进行了实证检验。本项目运用级联和社会传染的网络模型来分析谣言的传播。这些模型区分了简单传染和复杂传染，并预测简单传染无论网络拓扑如何都会传播，而复杂传染在小世界和无标度网络上的传播效率低于在内聚图上的传播效率。有效的信息，一个人即使从一个来源听到它也可能传播，是一个简单的传染的例子，而谣言，一个人在没有一些证实的情况下不愿意传播，是一个复杂的传染的例子。该项目将使用Netscan，一个从Usenet（一个基于互联网的讨论工具）收集的大量信息数据库，对谣言的传播和社会传染的网络模型进行实证研究。通过对谣言传播进行详细、系统的描述，并对理论模型产生的假设进行直接的实证检验，本研究将促进我们对社会传染的总体理解，特别是对谣言传播的理解。更广泛的影响：本研究的结果将对计算机科学和组织沟通等不同领域的研究产生影响。计算机安全专家、公司高管和政治领导人都在努力将谣言与经过证实的信息区分开来，并欢迎对它们的传播过程进行系统的比较。本研究将为本科生和少数族裔提供参与学术研究的机会，为社会学和信息科学专业的学生提供跨学科的研究经验。

This project studies the effects of network topology on the spread of rumor and makes three major intellectual contributions. First, it provides a theoretical framework for explaining the relationship between networks and the spread of rumor. Second, it provides an empirical investigation of the diffusion of rumor through networks, including a comparison with the transmission of valid information. Finally, this project offers an empirical test of hypotheses generated by leading theoretical research on network models of social contagion. The project applies network models of cascades and social contagion to analyzing the spread of rumor. These models differentiate between simple and complex contagions, and predict that simple contagions will spread regardless of network topology while complex contagions will spread less effectively on small-world and scale-free networks than on cohesive graphs. Valid information, which an individual is likely to pass along even after hearing it from one source, is an example of a simple contagion, while rumor, which an individual will be reluctant to pass along without some corroboration, is an example of a complex contagion.The project will use Netscan, a vast database of messages collected from Usenet, an Internet-based discussion tool, to empirically examine the spread of rumor and network models of social contagion. By providing both a detailed, systematic description of the spread of rumor and direct empirical tests of the hypotheses generated by the theoretical models, this study will advance our understanding of social contagion in general, and rumor transmission in particular.Broader Impact:The results of this study will have implications on research in areas as diverse as computer science and organizational communication. Computer security experts, corporate executives, and political leaders all contend with separating rumor from verified information, and would welcome a systematiccomparison of their diffusion processes. This research will offer opportunities for undergraduates and members of underrepresented minorities to get involved in academic research, providing cross-disciplinary research experience for students of sociology and information science.