标题： 预测分析在社会扩散中的作用：网络社区的作用 显示英文标题

标题： Predictive Analysis for Social Diffusion: The Role of Network Communities

摘要： 信息和行为在社交网络中的扩散在从社会学到计算机科学以及营销、金融、人类健康和国家安全等应用领域中引起了广泛的研究兴趣。 特别值得关注的是，开发社会扩散的预测能力的可能性，例如，能够早期识别那些可能变得“病毒式”传播并蔓延到人口很大一部分的扩散过程。 最近，我们通过理论分析表明，社会扩散的动力学可能在很大程度上取决于社交网络社区之间的相互作用，即个体之间连接紧密的群体，而这些群体之间的联系相对较少。 本文提出了一项实证研究，探讨由此发现得出的两个相关假设：1）跨社区的互动可以预测社会扩散的范围；2）扩散现象在网络社区之间的分散程度是一个有用的早期指标，表明传播可能会“成功”。 我们通过案例研究来探索这些假设，包括20世纪初瑞典社会民主党出现的情况、2002-2003年SARS病毒的传播，以及与现实世界抗议活动相关的博客动态。 这些实证研究证明，基于网络社区的扩散指标确实具有预测能力，事实上可能比标准测量方法更有用。 显示英文摘要

摘要： The diffusion of information and behaviors over social networks is of considerable interest in research fields ranging from sociology to computer science and application domains such as marketing, finance, human health, and national security. Of particular interest is the possibility to develop predictive capabilities for social diffusion, for instance enabling early identification of diffusion processes which are likely to become "viral" and propagate to a significant fraction of the population. Recently we have shown, using theoretical analysis, that the dynamics of social diffusion may depend crucially upon the interactions of social network communities, that is, densely connected groupings of individuals which have only relatively few links between groups. This paper presents an empirical investigation of two related hypotheses which follow from this finding: 1.) inter-community interaction is predictive of the reach of social diffusion and 2.) dispersion of the diffusion phenomenon across network communities is a useful early indicator that the propagation will be "successful". We explore these hypotheses with case studies involving the emergence of the Swedish Social Democratic Party at the turn of the 20th century, the spread of the SARS virus in 2002-2003, and blogging dynamics associated with real world protest activity. These empirical studies demonstrate that network community-based diffusion metrics do indeed possess predictive power, and in fact can be more useful than standard measures.