Collaborative Research: AccelNet: Accelerating Discovery in Multilevel Network Science

合作研究：AccelNet：加速多层次网络科学的发现

• 批准号: 1927418
• 负责人: Santo Fortunato
• 金额: $ 97.99万
• 依托单位: Indiana University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2019
• 资助国家: 美国
• 起止时间: 2019-10-01 至 2025-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1927418&HistoricalAwards=false
• 关键词: Collaborative; Research; AccelNet; Accelerating; Discovery

1927418 (Fortunato) 1927425 (Vespignani). Humans live in an increasingly connected world. And data on networks that capture connections of transportation, trade, health, and communication are increasingly available. These data offer scientists a chance to tackle some of society's greatest problems, such as infectious disease, fake news, natural disasters, cyber-attacks, and health care. However, advances in network science rely on improved mathematical and theoretical approaches to properly model complex systems with multiple, interdependent network layers. To address this, AccelNet-MultiNet aims to link international expertise and provide formal infrastructure for joint US-Europe scientific discovery in the field of multilevel, multilayer networks. This network of networks will result in new methods and models to address societal challenges and the next generation of networks science leaders.The scientific agenda of this AccelNet project focuses on two promising areas in network science: (1) theory and methodology, specifically temporality, embeddings in vector space, information-richness, reaction-diffusion processes; and (2) applications, including characterizing and modeling the societal multiplex, multilayer and multi-omics biological network analysis, resilience management during biological threats. A key feature of AccelNet-MultiNet?s suite of training and collaboration tools will be an intensive Fellows program. These 40 graduate students and postdoctoral researchers will participate in a year-long webinar series open to the larger scientific community, annual large-scale collaborative problem-solving activities (Collabathons), and a semester-long immersive exchange program. In addition, international leader meetings will bring together partners and additional experts to set the agenda for the future of the multilayer, multilevel networks field. These will result in Future Directions Research reports outlining research priorities, strategies, and shared educational vision in the field. An International Communication Competency training toolkit will be developed to help scholars build basic skills for successful cross-cultural, cross-national collaborations. Materials will be made publicly available through a web-based portal, including the training toolkit, community-developed reports, publications, webinar talks, and shared data sets. The Accelerating Research through International Network-to-Network Collaborations (AccelNet) program is designed to accelerate the process of scientific discovery and prepare the next generation of U.S. researchers for multiteam international collaborations. The AccelNet program supports strategic linkages among U.S. research networks and complementary networks abroad that will leverage research and educational resources to tackle grand scientific challenges that require significant coordinated international efforts.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.

1927418（马拉托）1927425（维斯皮纳尼）。人类生活在一个日益互联的世界。网络上捕捉交通、贸易、健康和通信联系的数据越来越多。这些数据为科学家提供了解决一些社会最大问题的机会，例如传染病，假新闻，自然灾害，网络攻击和医疗保健。然而，网络科学的进步依赖于改进的数学和理论方法，以正确建模具有多个相互依赖的网络层的复杂系统。为了解决这一问题，CNONet-MultiNet旨在将国际专业知识联系起来，并为美欧在多层次、多层网络领域的联合科学发现提供正式的基础设施。这个网络的网络将导致新的方法和模型，以解决社会的挑战和下一代的网络科学leader.The科学议程的网络科学集中在两个有前途的领域：（1）理论和方法，特别是时间性，嵌入在向量空间，信息丰富性，反应扩散过程;（2）应用，包括社会多元性、多层次和多组学生物网络分析、生物威胁下的恢复力管理等。MultiNet的一个关键特性？的培训和协作工具套件将是一个密集的研究员计划。这40名研究生和博士后研究人员将参加为期一年的网络研讨会系列，向更大的科学界开放，年度大型协作解决问题活动（Collabathons），以及为期一个学期的沉浸式交流计划。此外，国际领导人会议将汇集合作伙伴和其他专家，为多层次，多层次网络领域的未来制定议程。这些将导致未来方向研究报告概述了研究重点，战略和共同的教育愿景在该领域。将开发一个国际交流能力培训工具包，以帮助学者建立成功的跨文化，跨国合作的基本技能。材料将通过一个网络门户向公众提供，包括培训工具包、社区编写的报告、出版物、网络研讨会讲座和共享数据集。通过国际网络对网络合作加速研究（CNONet）计划旨在加速科学发现的过程，并为下一代美国研究人员进行多团队国际合作做好准备。 该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Emergent local structures in an ecosystem of social bots and humans on Twitter

• DOI: 10.1140/epjds/s13688-023-00406-5
• 发表时间: 2023-09-22
• 期刊: EPJ DATA SCIENCE
• 影响因子: 3.6
• 作者: Alrhmoun，Abdullah;Kertesz，Janos
• 通讯作者: Kertesz，Janos