Graphische Darstellung der Anpassungsgüte akteursbasierter Netzwerkentwicklungsmodelle

对于统计模型的诊断，已经提出了大量的图解方法。主要的动机是，这样的模型在他们的假设中往往是相当严格的，并且很难评估在经验数据集和假设匹配该数据的统计模型之间的哪些方面存在重要的偏差。对于数据的人眼特征和数据模型组合的特征，提出了图形方法，这些特征不容易被其他手段辨别，并且可能指向模型不能很好地表示的数据的方面。在社会网络分析中，图形表示从一开始就是最重要的，因为在可视化中，网络结构的复杂性通常可以比通过代数属性或数值描述参数更清楚地表现出来。另一方面，目前还没有现成的方法来可视化演化网络以支持可靠的模型评估，本项目的目的是开发和使用网络可视化方法来解释和诊断社会网络演化的统计模型。Snijders的模型[28，以及总体项目提案中列出的相关出版物]构成了我们的ECRP提案的基础，它们是相当代数的，需要更容易地使用补充的图形方法。这些方法将与核心建模项目以及我们以实质性和经验性为导向的合作伙伴项目一起在反馈循环中开发。

A large number of graphical methods have been proposed for the diagnosis of statistical models. The,primary motivation is that such models are often quite restrictive in their assumptions, and it is difficult to assess in which aspects there is an important deviation between an empirical data set and a statistical model supposed to match this data.Graphical methods are present to the human eye features of the data, and features of the datamodel combination, that are not easily discerned by other means and that may point to aspects of the data that are not well represented by the model. The simultaneous graphical exploration of model, data, and fit may lead to finding and fitting a better model.In social network analysis, graphical representations have been of paramount importance from the very beginning, since the complexity of a network structure can often be brought out much more clearly in a visualization than by algebraic properties or numerical descriptive parameters. On the other hand, there are no readily available methods for visualizing evolving networks so as to support reliable model evaluation.The aim of this project is to develop and employ network visualization methods for the interpretation and model diagnosis of statistical models for social network evolution. The models of Snijders [28, and related publications listed in the overall project proposal], which form the basis of our ECRP proposal, are rather algebraic and require complementary graphical methods to be utilized more easily. These methods will be developed in a feedback-loop with both the core modeling project and our substantively and empirically oriented partner projects.