U.S.- Hungary Research on Social Networks as Evolving Complex Networks

这个由卡拉马祖学院的Jan Tobochnik和布达佩斯Eotvos大学的George Kampis合作的美国-匈牙利研究项目的目标是研究社会网络的结构和动态。他们将从一个简单的社会网络形成和发展模型开始，其中包括具有影响其与其他节点连接方式的属性或特征的单个节点。接着，研究人员将把他们的抽象模型与通过调查学生建立的友谊网络的实证数据进行比较。将模型和调查结果进行比较，以确定形成连接的概率是否与两个节点之间的相似性函数成正比。通过观察某些物理性质，如从许多簇到单个簇的相变作为控制参数的函数，研究结果将改进新兴网络特性的定义，特别是网络的聚类和分层结构。我们还将考虑移除随机节点的影响以及一些基于游戏的效率措施观察结果。总的来说，新的跨学科方法应该通过美国-匈牙利专家在系统建模、认知机制和计算数学方面的贡献来加强当前网络的社会科学工作。预计研究结果将改进目前审查实际实体（如人、组织和社区）之间关系的方法。这项对不断发展的复杂网络的研究实现了推进科学知识的计划目标，使美国和中欧的专家能够结合互补的人才，并在共同感兴趣和有能力的领域共享研究资源。更广泛的影响还包括通过在匈牙利机构的工作和直接参与该项目的中央网络调查，向美国学生介绍跨学科科学和国际研究界。

The goal of this U.S.-Hungarian research project between Jan Tobochnik of Kalamazoo College and George Kampis of Eotvos University, in Budapest, is to study the structure and dynamics of social networks. They will begin with a simple model for the formation and growth of a social network that includes individual nodes with properties or traits that influence how they connect with other nodes. In turn, the researchers will compare their abstract model with empirical data from friendship networks created through surveys of students. The model and survey results will be compared to determine if the probability of forming a connection is proportional to a function of similarity between two nodes. Results should improve the definition of properties of emerging networks, especially the clustering and the hierarchical structure of networks, through observations of certain physical properties such as phase transition from many clusters to a single cluster as a function of control parameters. The effects of removing random nodes and some game-based observations of efficiency measures will be considered as well. Overall, the novel interdisciplinary approach should strengthen current social science work on networks through US-Hungarian expert contributions in systems modeling, mechanisms of cognition, and computational mathematics. Results are expected to improve present methods for examining relationships between real entities such as people, organizations and communities. This research on evolving complex networks fulfills the program objective of advancing scientific knowledge by enabling experts in the United States and Central Europe to combine complementary talents and share research resources in areas of strong mutual interest and competence. Broader impacts also include the introduction of U.S. students to interdisciplinary science and to the international research community through work at Hungarian institutions and direct involvement with the project's central network survey.