由於網際網路的蓬勃發展,越來越多人以社群網路作為溝通的工具。如此造就越來越多的社群網站的興起,例如:Myspace、Twitter、 Plurk、Facebook(臉書)等。在社群網路中,使用者在做決策時,通常會受到朋友訊息的影響,同時也會分享自我訊息,進一步影響到朋友的決策。 本篇論文希望藉由模擬的方式,探討社群網路上的訊息是如何影響使用者做決策的。我們將以使用者加入臉書粉絲團之行為模式作為實驗。從實驗結果中發現,當使用者加入某一個臉書粉絲團時,其已加入該粉絲團的朋友數量將呈現Poisson 分佈。再者,實驗結果也顯示臉書粉絲團的會員數量的發生頻率具有Power law的特性。
With the progression of internet, people have increasingly relied on social network as a means of communication. As a result, more and more social networking sites such as Myspace, Twitter, Plurk, and Facebook are popping up. In social network, users usually get to make decisions based on which messages their friends conveyed and also share their messages to influence the decisions of their friends. This thesis develops simulation models to analyze how message influence affects users’ decision making in social network. We experiment with the behavior of users when they join fan pages on Facebook. The experimental results show that when a user joins a fan page, the number of his/her friends who are already members of that fan page is a Poisson distribution. Furthermore, the experimental results produce a Power law frequency distribution for the size of fan pages on Facebook.