CRII: CHS: Early Detection of Collective Misconceptions with Network-aware Machine Learning Tools

CRII：CHS：使用网络感知机器学习工具及早发现集体误解

• 批准号: 1755873
• 负责人: Emoke-Agnes Horvat
• 金额: $ 17.48万
• 依托单位: Northwestern University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-03-15 至 2021-02-28
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1755873&HistoricalAwards=false
• 关键词: CRII; CHS; Early; Detection; Collective

This project builds theory, algorithms, and frameworks that can be used to design network-aware machine learning tools aimed at eliciting useful diversity and improving the accuracy of collective forecasting. Researchers in the social and economic sciences know that there is great capacity for collective intelligence to emerge from Web-based systems. Yet herding and homophily effects often restrain the wisdom of crowds, vastly limiting this potential. The research furthers the study of complex systems by introducing a new framework that improves our understanding of the mechanisms that govern decision-making under social influence. Advancing complex systems theory in this way greatly enhances the ability to predict when crowds will provide accurate decision-making support for complex problems and when they will fail miserably. Further, the research aids the development of opinion aggregation mechanisms that efficiently capitalize on diversity. The planned work will result in developments that make collective intelligence detection tools practical by providing early warning signs of shared misconceptions. To attain these goals, the research will apply a general framework that incorporates (1) network models that help understand the social processes that lead to observed decision patterns; (2) machine learning tools that draw from uncovered processes to identify signals that optimize the accuracy of collective judgment; and (3) evaluation testbeds that use simulation tools in addition to rich high-dimensional, real-world data about the various stages and performance of group decisions. This research will contribute to societally-relevant outcomes, including: (a) understanding decision-making in online investment and lending settings to enhance the economic growth of underserved market segments; (b) generating novel knowledge about the performance benefits of collective judgment, and (c) quantifying the link between limited opinion diversity and crowd misconceptions. The project will connect undergraduate students, including women and under-represented minorities, to authentic practice in science and engineering research.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.

该项目建立了理论，算法和框架，可用于设计网络感知机器学习工具，旨在引发有用的多样性和提高集体预测的准确性。社会和经济科学的研究人员知道，基于网络的系统具有很大的集体智慧能力。然而，羊群效应和同质性效应往往抑制了群体的智慧，极大地限制了这种潜力。这项研究通过引入一个新的框架来进一步研究复杂系统，该框架提高了我们对社会影响下决策机制的理解。以这种方式推进复杂系统理论，可以大大提高预测群体何时会为复杂问题提供准确的决策支持，以及何时会惨败的能力。此外，研究有助于发展有效利用多样性的意见聚合机制。计划中的工作将通过提供共同误解的早期预警信号，使集体情报探测工具变得实用。为了实现这些目标，该研究将应用一个通用框架，该框架包括：（1）网络模型，有助于理解导致观察到的决策模式的社会过程;（2）机器学习工具，从未发现的过程中提取信息，以识别优化集体判断准确性的信号;以及（3）评估测试平台，除了使用关于群体决策的各个阶段和性能的丰富的高维真实世界数据之外，还使用模拟工具。 这项研究将有助于社会相关的成果，包括：（a）了解在线投资和贷款环境中的决策，以促进服务不足的细分市场的经济增长;（B）产生关于集体判断的绩效效益的新知识，以及（c）量化有限的意见多样性和人群误解之间的联系。该项目将连接本科生，包括妇女和代表性不足的少数民族，在科学和工程研究的真实实践。这个奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

项目成果

Gender Differences in the Global Music Industry: Evidence from MusicBrainz and The Echo Nest

• DOI: 10.1609/icwsm.v13i01.3249
• 发表时间: 2019-07
• 作者: Yixue Wang;Emőke-Ágnes Horvát

(Un)intended consequences of networking on individual and network-level efficiency

网络对个人和网络层面效率的（非）预期后果

• DOI: 10.1007/s41109-019-0196-2
• 发表时间: 2019
• 期刊: Applied Network Science
• 影响因子: 2.2
• 作者: Tanaka, Kyosuke;Horvát, Emőke-Ágnes
• 通讯作者: Horvát, Emőke-Ágnes

Investor Retention in Equity Crowdfunding

• DOI: 10.1145/3292522.3326037
• 发表时间: 2019-06
• 期刊: Proceedings of the 10th ACM Conference on Web Science
• 作者: Igor Zakhlebin;Emőke-Ágnes Horvát

Network Perspective on the Efficiency of Peace Accords Implementation

和平协议执行效率的网络视角

• 发表时间: 2020
• 期刊: Proceedings of the International Conference on Advances in Social Network Analysis and Mining
• 作者: Dambanemuya, Henry K.;Joshi, Madhav;Horvát, Emőke-Ágnes
• 通讯作者: Horvát, Emőke-Ágnes

Harnessing Collective Intelligence in P2P Lending

在 P2P 借贷中发挥集体智慧

• DOI: 10.1145/3292522.3326040
• 发表时间: 2019
• 期刊: WebSci '19: Proceedings of the 10th ACM Conference on Web Science
• 作者: Dambanemuya, Henry K.;Horvát, Emoke-Ágnes
• 通讯作者: Horvát, Emoke-Ágnes