Rödder Wilhelm, Dellnitz Andreas, Kulmann Friedhelm, Litzinger Sebastian, Reucher Elmar
Department of Operations Research, FernUniversität in Hagen, 58097 Hagen, Germany.
Department of Quantitative Methods, FernUniversität in Hagen, 58097 Hagen, Germany.
Entropy (Basel). 2019 Mar 13;21(3):277. doi: 10.3390/e21030277.
A special type of social networks is the so-called affiliation network, consisting of two modes of vertices: actors and events. Up to now, in the undirected case, the closeness of actors in such networks has been measured by their jointly-attended events. Indirect contacts and attenuated and directed links are of minor interest in affiliation networks. These flaws make a veritable estimation of, e.g., possible message transfers amongst actors questionable. In this contribution, first, we discuss these matters from a graph-theoretical point of view. Second, so as to avoid the identified weaknesses, we propose an up-and-coming entropy-based approach for modeling such networks in their generic structure, replacing directed (attenuated) links by conditionals: if-then. In this framework, the contribution of actors and events to a reliable message transfer from one actor to another-even via intermediaries-is then calculated applying the principle of maximum entropy. The usefulness of this new approach is demonstrated by the analysis of an affiliation network called "corporate directors".
一种特殊类型的社交网络是所谓的归属网络，它由两种顶点模式组成：参与者和事件。到目前为止，在无向情况下，此类网络中参与者的亲近程度是通过他们共同参与的事件来衡量的。间接联系以及弱化和有向链接在归属网络中不太受关注。这些缺陷使得对例如参与者之间可能的信息传递进行准确估计变得可疑。在本论文中，首先，我们从图论的角度讨论这些问题。其次，为了避免已识别的弱点，我们提出一种新兴的基于熵的方法，用于对这类网络的一般结构进行建模，用条件（如果 - 那么）取代有向（弱化）链接。在这个框架中，然后应用最大熵原理计算参与者和事件对从一个参与者到另一个参与者（即使通过中介）的可靠信息传递的贡献。通过对一个名为“企业董事”的归属网络的分析，证明了这种新方法的有效性。
