近年來有大量的研究著重於利用使用者訊息在社群網路中傳播的行為，來評估社群之中個別使用者之影響力，以期利用來支援口碑行銷。然而在過往針對影響力評估之研究中，通常都只著重於使用者之間的傳播行為，並未考慮到使用者所屬社群之間的傳播行為。因此本研究為提供一個有系統性之訊息傳播規則評估方式，將依據如下三個模組來漸次的建構階層式訊息傳播路徑探勘系統，以期望從最細微之使用者訊息傳播規則到最巨觀之社群間傳播規則皆能發掘出來，以供企業做口碑行銷時使用。 本研究分為三個部分：第一部分將根據使用者過去所轉貼的文章，來定義使用者所屬的社群為何；第二部分利用序列探勘演算法找出社群網路中使用者之間訊息傳播之行為，並將使用者之間的傳播路徑以最合理之方式切割；第三部分設計一階層式字尾樹演算法，結合概念化階層探勘出不同細緻程度階層社群之間的訊息傳播規則。 最後，本研究將提出多種應用，可支援企業在網路行銷上的使用，能有效的滿足業者該如何以最小的預算，達到最大的行銷效益。 In order to evaluate the influence of single user in a society to support marketing, many researches focus on the behavior of propagating user messages in social network in recent years. However, most of the researches of influence evaluation in the past focused on the behavior of propagating between users, instead of considering the behavior of propagating between different social communities. Hence, this research provides a system to evaluate the pattern of propagating messages. We construct a hierarchical information propagating path mining system, expecting it could help discovering the pattern of information propagating paths from between users to between communities. This research is composed of three parts: the first will define which social community the user belongs to by the articles he/she posted in the past; the second part we employ sequence mining algorithm to find the pattern of how users propagate information between each other, and cut the propagation path apart in a reasonable way; in the third part we design a Generalized Propagation Suffix Tree algorithm, combine it with concept hierarchy to discover the propagation paths of user or community in different granularity. Finally, we propose some applications to support web marketing for enterprises to spent less cost to reach maximum benefits.
