在現今的社會中，訊息傳遞由於網路的發達而更加快速，因此在網路中進行訊息投放的目標選擇好壞將會大大影響一則訊息傳播的成本及效率。在本篇論文中，將著重於探究在社群網路中的最大擴散率問題(Influence maximization)，我們會從最基本的中心度(centrality)開始延伸到特徵點群集(key point player)。接著探討特徵點群集中所衍生的缺點跟可改進之處，最後套入分群概念，提出一個新的分群特徵點方法使得效能以及最大化擴散率兩者之間能夠兼具。

In today's society, since the Internet development, the transmission of information has been faster and faster.
Thus, the choice of the target of the message in the network will greatly affect the cost and efficiency of a message.
In this paper, we will analyze the influence maximization problem in the social network. First we will extend from the most basic centrality to the key players set.
Then we discuss the shortcomings in the key point players set. Finally, we import the concept of clustering and propose a new method of clustering key player points so that we can take care both performance and maximum diffusion rate.

Introduction -----1
Related work -----3
Model ------------10
Method -----------13
Experiment -------20
Conclusions ------24
Bibliography------26

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