In many networks, the indegree of a vertex is a measure of its popularity. Past research has studied indegree distributions treating the network as a whole. In the US Patent citation network (USPCN), patents are classified into categories and subcategories. A natural question arises: How do patents gather their popularity from various (sub)categories? We analyse local indegree distributions to answer this question. The citation (indegree) of a patent within the same category indicates its internal popularity, while a cross-category citation indicates its external popularity. We analyze the internal and external indegree distributions at each level of USPCN hierarchy to learn how the internal and external popularity of patents varies across (sub)categories. We find that all (sub)categories have local preferences that decide internal and external patents' popularities. Different patents are popular in different groups: Groups C1, C2 and C3 may not agree on popular patents in C1. In general, patent popularity appears to be a highly local phenomenon with subcategories (not even categories) deciding their own popular patents independent of the other (sub)categories.
翻译:在许多网络中,一个顶点的度量是其受欢迎程度的衡量标准。过去的研究研究了整个网络的度分布。在美国专利引用网(USPCN)中,专利被分为类别和亚类。自然产生的一个问题是:专利如何从各种(子)类别中获得受欢迎程度?我们分析一个同一类别中的当地度分布来回答这个问题。同一类别中的专利的引用(度)表明其内部受欢迎程度,而跨类引用则表明其外部受欢迎程度。我们分析了美国专利引用网各级的内部和外部度分布,以了解专利在各种(子)类别中的内部和外部受欢迎程度如何不同。我们发现,所有(子)类别都具有决定内部和外部专利受欢迎程度的本地偏好,决定内部和外部的普惠性。不同的类别是:C1组、C2组和C3组可能不同意在C1中流行专利。一般而言,专利受欢迎程度似乎是一种具有子类别(甚至类别)的高度本地现象,决定它们自己的专利独立于其他(子)类别。