Information Diffusion Between Two Networks

不同群体之间达成一致的速度受到人们处理信息的方式的严重影响。许多论文关注的是收敛到共识的速度，一个基本的想法是，隔离（如种族隔离）减缓收敛，但很少有人探讨如何加速它。此外，现有的网络学习理论严重依赖于经济学以外的原则（如图论和组合技术），而没有明确建模行为所产生的激励。我的研究计划文件，我的目标是如何填补这一空白，提供一个透彻的了解信息处理机制如何影响收敛的速度，并设计一个有效的机制来推断隔离的效果，加快共识，其中个人的激励和行为被考虑在内。达成共识的速度对社会福利很重要。例如，皮尤研究中心（Pew Research Center，2006年）的一项研究发现，只有大约41%的人认为人类活动是全球变暖的主要原因，而21%的人认为自然模式导致了全球变暖。不同群体中的个体具有相似的不完全信息偏差，基于这些信息，他们形成了不同的信念，导致不同的反应。解决这些问题符合每个人的利益，但只有通过信息和信念的融合（共识）才能实现。这项研究的一个重要部分也是激励措施在趋同过程中发挥的作用。许多社会学习理论在解释信息扩散的微观随机过程时，仅仅是基于数学工具。在这些理论中，个人激励的遗漏排除了福利和政策分析。然而，一旦考虑到激励因素，有效的信息处理方法可以通过避免不必要的成本来增加社会福利。我打算研究隔离网络，并考虑信息处理，有效地利用信息，以限制收敛过程到一个合理的时间。将这些特征归纳为一个新的理论框架是本研究的第一部分。其基本思想是，了解世界的真实状态是社会最佳状态，但人们只能通过社会关系传递信息。这一框架有助于我调查达成协议的时间使用短视的最佳应对策略和rationalfarsighted策略。本研究的第二部分将探讨一种有效的信息处理策略，通过在实际问题中考虑激励因素来促进共识。第一步是过滤出有效的信息，以避免重复会计时，人们暴露在重叠的信息。下一步是定义一个宽松的共识，即人们的信仰仍然可以有距离。虽然大多数理论都任意设置了一个数学参数，但我将使用激励来设置距离。

The speed of reaching an agreement between distinct groups is heavily affected by the way people are processing information. Many papers focus on the speed of converging to the consensus, and a basic idea is that segregation (such as ethnic segregation) slows the convergence, but very few explored how to accelerate it. Furthermore, existing network learning theories depend heavily upon principles outside of economics (like graph theory and combinatorial techniques) without explicitly modelling behaviours arising from incentives. My research proposal documents how I aim to fill this gap by providing a thorough understanding of how information processing mechanisms affect the speed of convergence and designing an efficient mechanism to deduce the effect of segregation and speed up consensus in which individuals'incentives and behaviours are taken into account. The speed to consensus is important for social welfare. Consider for example a Pew Research Center (2006) study that found only about 41% of people believe human activities are the main reason for global warming, whereas 21% believe natural patterns cause it. Such disagreement concerning factual questions stems from differences in information. Individuals in different groups have similarly biased incomplete information, and based on the information, they form divergent beliefs leading to different reactions. Solving these problems is in the interest of everyone butcan only be reached through convergence of information and beliefs (consensus). An important part of this research is also what role incentives play in the process of convergence. Many social learning theories are only based on mathematical tools in explaining the micro-level stochastic process of information diffusion. The omission of individual incentives in those theories precludes welfare and policy analysis. However, once incentives are taken into account, efficient information processing methods canincrease social welfare by avoiding unnecessary costs. I intend to study segregated networks and think about information processing that makes use of information effectively to restrict the convergence process to a reasonable time. Incorporating these features into a novel theoretical framework is the first part of this research. The basic idea is that knowing the true state of the world is socially optimal but people can only convey information through social ties. This framework helps me in investigating the time of reaching an agreement using a myopic best-responding strategy and a rationalfarsighted strategy. The second part of this research will explore an efficient information processing strategy that facilitates consensus by taking incentives into account in practical problems. The first step is to filter out valid information to avoidrepeated accounting when people are exposed to overlapping information. The next step is to define a relaxed consensus that people's beliefs can still have distance. While most theories arbitrarily set a mathematical parameter, I will use incentives to set up the distance.