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CAREER: A Holistic Framework for the Analysis of Information Dynamics in Human Networks

职业：人类网络信息动态分析的整体框架

基本信息

批准号：
2048042
负责人：
Emrah Akyol
金额：
$ 59.63万
依托单位：
SUNY at Binghamton
依托单位国家：
美国
项目类别：
Continuing Grant
财政年份：
2021
资助国家：
美国
起止时间：
2021-02-15 至 2026-01-31
项目状态：
未结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=2048042&HistoricalAwards=false
关键词：
CAREER Holistic Framework Analysis Information

项目摘要

Communications between humans is different from communications between machines due to cognitive limitations, biases, and misaligned objectives, yet human behavior is still predictable in a statistical sense. Motivated by this observation, this project investigates problems of theoretical and practical significance concerning human communication networks. Typical scenarios include human-machine systems and social networks where selfish agents, some of whom are prone to bias and limitations, control nodes to manage information flow to maximize their own perceived payoff. While relevant models have been studied in the field of Behavioral Economics, their extensions to realistic communication and control settings pose many open problems. This project will adopt a holistic approach that considers an end-to-end problem jointly from information, control, and game-theoretic perspectives, leveraging tools and models from all three disciplines. A notable application of the developed framework is on modeling public opinion polarization and misinformation spread over social networks. Another application pertains to mitigating the impact of bias in information processing systems. The work will address fundamental questions regarding the emerging human communication paradigm. This growing research field requires revisiting key results in classical communication and control theories and poses significant challenges, requiring approaches and tools from multiple disciplines. The research outcomes are expected to constitute an essential step in understanding the interplay of game theory and economics with information theory, control, communications, and compression. Specific goals of this project are categorized into three groups. The first set of goals investigates communication and compression problems between agents with misaligned objectives, cognitive limitations, and biases. The second set of goals concerns behavioral linear averaging models of opinion evolution and their applications in polarization dynamics. The final set of goals explores truthful data gathering strategies in behaviorally biased information networks.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

由于认知限制、偏见和目标错位，人与人之间的沟通不同于机器之间的沟通，但人类的行为在统计意义上仍然是可预测的。在这一观察的推动下，本项目研究了与人类通信网络有关的具有理论和实践意义的问题。典型的场景包括人机系统和社交网络，在这些场景中，自私的代理(其中一些容易受到偏见和限制)控制节点管理信息流，以最大化自己感知的回报。虽然行为经济学领域已经研究了相关模型，但它们对现实交流和控制环境的扩展提出了许多悬而未决的问题。该项目将采用一种全面的方法，从信息、控制和博弈论的角度联合考虑端到端问题，利用所有这三个学科的工具和模型。开发的框架的一个值得注意的应用是对社会网络上的舆论两极分化和错误信息传播进行建模。另一项申请涉及减轻信息处理系统中的偏见的影响。这项工作将解决有关新兴人类交流范式的基本问题。这一不断增长的研究领域需要重新审视经典通信和控制理论中的关键成果，并提出了重大挑战，需要来自多个学科的方法和工具。这些研究成果有望成为理解博弈论和经济学与信息理论、控制、通信和压缩的相互作用的重要一步。该项目的具体目标分为三组。第一组目标调查目标未对齐、认知限制和偏见的代理之间的通信和压缩问题。第二组目标涉及意见演化的行为线性平均模型及其在极化动力学中的应用。最后一组目标探索了行为偏见信息网络中的真实数据收集策略。这一奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。