在這篇論文中，我們探討了社群網路結構的問題，並此架構了一網路模型。在這模型中，我們首先利用現有的G(n,p)模型與Configuration 模型，並在此模型上，對每個節點都會有機會與自己本身朋友的朋友形成額外的鍵結，我們將此種規則命名為：Triad Formation。在此篇論文中，我們在這兩種模型上並加上自己定立的規則，推導其平均節點分支度(Degree)、分支度的分布與群聚係數。在此，我們利用兩個變數來同時調控平均節點分支度與群聚係數。

In this paper we consider the network formation problem of social networks. In this model,
every vertex is asked to establish an edge with the second neighbor with a probability on
the Erd˝os-R´enyi model and the configuration model respectively. We call this operation
triad formation. We derive the mean degree, degree distribution and the clustering
coefficient of these two models. Here, we use two parameters to match the networks of
given mean degrees and clustering coefficients simultaneously.

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