由於近年社群網路各種應用網站興起，像是Facebook、Twitter，等，相關議
題也逐漸受到討論，例如越來越多利用社群網路傳播訊息或者病毒式行銷的相關
研究。當我們能夠找出一個社群網路當中，習慣的傳播模式或者是傳播路徑，並
且能從中定位各種角色的重要性，進一步在社群網路中找出這些角色後，在這些
相關的議題的應用將更加靈活。
目前各大社群網路應用網站，使用者都可以與社群網路中的好友分享自己的
動作，例如發佈影片或圖片，評論，按「讚」等，基於這樣的前提使用者的任何
活動是有機會被社群網路中的好友影響，因此我們定義好友間影響的可能性，以
及依觀察合理的定義出社群網路中較為重要的角色。
我們的演算法經由收集使用者在固定社群網路應用網站的各種動作，加上動
作的時間所形成的動作誌(action log)，以及使用者們所構成的社群網路，可以從
社群網路中找出主要的資訊傳遞路徑以及各種不同限制下的領袖以及追隨者，並
且將會利用社群網路應用網站驗證分析我們所定義的角色成為結論。

Recently, social networking services and websites such as Facebook
and Twitter are taking more and more parts in our daily life. Issues
of in
uence propagation have been studied in recent years. To ll
in the gap of previous works, we aim to discover the main path
of in
uence and dene the importance of leader in hierarchy on
the social graph. Social networking users are in
uenced by the
power of social networking service as they are able to post and
likevideos, pictures and comments. Therefore, in this study we
propose to discover the possibility of a relation and important roles by
mining social activities. After collecting performed action and time
stamp from dierent users and understanding their social network,
our framework was able to identify the main in
uence paths and
leaders under dierent constrains. Most importantly, our approach
outperforms both on precision/recall and ranking in realistic data.

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