标题： 一个蓝色起点：大规模二元及高阶社会网络数据集 显示英文标题

标题： A Blue Start: A large-scale pairwise and higher-order social network dataset

摘要： 大规模网络对于塑造我们关于个体如何相互作用的看法至关重要，在数学流行病学、计算社会科学和生物学中也产生了关键的见解。 然而，许多通过疾病传播、信息扩散以及个体互动的基础社会系统本质上是通过任意规模的群体（即高阶交互）来中介的。 在群体形成与分裂的高阶动力学、传染病传播和社会影响之间，存在与验证这些高阶机制所需数据之间的差距。 同样地，很少有数据集能够弥合这种二元网络数据和高阶网络数据之间的鸿沟。 由于其开放的应用程序编程接口（API），Bluesky 社交媒体平台为观察大规模社交关系提供了一个实验室。 除了成对的关注关系外，与许多其他社交网络不同，Bluesky 还以用户自定义的“起始包”列表作为社交网络扩展的机制。 我们推出了“蓝起点”（A Blue Start）这一大规模网络数据集，该数据集包含 2670 万用户及其 16 亿个成对关注关系，以及 30.13 万个代表“起始包”的群体。 此数据集将成为高阶网络科学研究的重要资源。 显示英文摘要

摘要： Large-scale networks have been instrumental in shaping the way that we think about how individuals interact with one another, developing key insights in mathematical epidemiology, computational social science, and biology. However, many of the underlying social systems through which diseases spread, information disseminates, and individuals interact are inherently mediated through groups of arbitrary size, known as higher-order interactions. There is a gap between higher-order dynamics of group formation and fragmentation, contagion spread, and social influence and the data necessary to validate these higher-order mechanisms. Similarly, few datasets bridge the gap between these pairwise and higher-order network data. Because of its open API, the Bluesky social media platform provides a laboratory for observing social ties at scale. In addition to pairwise following relationships, unlike many other social networks, Bluesky features user-curated lists known as "starter packs" as a mechanism for social network growth. We introduce "A Blue Start", a large-scale network dataset comprising 26.7M users and their 1.6B pairwise following relationships and 301.3K groups representing starter packs. This dataset will be an essential resource for the study of higher-order network science.