Information Diffusion Between Two Networks

两个网络之间的信息传播

• 批准号: 2713285
• 金额: --
• 依托单位: University of Edinburgh
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2713285
• 关键词: Information; Diffusion; Between; Two; Networks

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.

不同群体之间达成协议的速度在很大程度上受到人们处理信息的方式的影响。许多论文关注的是趋同的速度，一个基本的观点是，种族隔离（如种族隔离）减缓了趋同的速度，但很少有人探讨如何加快趋同的速度。此外，现有的网络学习理论严重依赖于经济学以外的原理（如图论和组合技术），而没有明确地建模由激励引起的行为。我的研究计划记录了我如何通过提供对信息处理机制如何影响趋同速度的透彻理解来填补这一空白，并设计了一种有效的机制来推断隔离的影响，并在考虑个人激励和行为的情况下加速达成共识。达成共识的速度对社会福利很重要。例如，皮尤研究中心（2006）的一项研究发现，只有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。这种关于事实问题的分歧源于信息的差异。不同群体的个体拥有同样偏颇的不完全信息，基于这些信息，他们形成了不同的信念，导致了不同的反应。解决这些问题符合每个人的利益，但只能通过信息和信念的融合（共识）来实现。本研究的一个重要部分也是激励在趋同过程中所起的作用。许多社会学习理论仅仅基于数学工具来解释信息扩散的微观随机过程。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，思考如何有效地利用信息将收敛过程限制在合理的时间内。将这些特征整合到一个新的理论框架中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优的，但人们只能通过社会关系来传递信息。这个框架帮助我用短视的最佳应对策略和理性的高瞻远瞩的策略来调查达成协议的时间。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。第一步是过滤掉有效的信息，以避免当人们接触到重叠的信息时重复记账。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。虽然大多数理论都是随意设置一个数学参数，但我将使用激励来设置距离。