由於資訊科技的發達，愈來愈多業者所推出的產品促銷活動開始趨向與社群 網站做結合，透過偌大的網際網路以及成千上萬的使用者將訊息傳播到世界各 地，加強了口耳相傳的產品行銷效果。若能從廣大的使用者社群當中，確認出社 群網路中的權威人士，也就是具有影響力之使用者，並且透過這類使用者傳播訊 息，將能大幅提高訊息的傳播效率。本研究運用Cost-Effective Lazy Forward (CELF) 演算法確認社群網路之具影響力使用者，並透過實驗確認其有效性。首先透過使 用者間之好友關係建構出節點連線模型，依照使用者好友之影響力程度，轉化為 影響力機率並代入CELF 演算法內，透過獨立串連模型的擴散模式，確認出影響 力較大的節點，並認定為社群網路中具影響力使用者。實驗平台採用臉書 (Facebook)建立主題性社團，以驗證此演算法的有效性。經由五週實際觀察社團的 發文和關注情況並且蒐集與分析數據，再以假設檢定確認演算法與實驗的相似 性，結果顯示運用CELF 演算法所確認的具影響力使用者，在發文所受到的關注 度確實比其他使用者為高。

Now days, people communicate not only with face to face but also with instant messages and online social networks. Millions of messages spread to the world through the Internet. Therefore, if we could identify influential users and let them disseminate information through the social networks, this way will substantially increase the message spreading efficiency. This study proposed to use Cost-Effective Lazy Forward (CELF) algorithm to identify influential users in a web social network, and the effectiveness of this algorithm was evaluated by an experiment. First the node connection model was built based on the relationship between users, the influence degrees were collected from the user survey, and they were calculated as influence probability between users. Using the independent cascade model in the CELF algorithm, this method can identify influential nodes as influential users in this web social network. The next stage is to verify the proposed method and an experiment was performed in Facebook for five weeks. All interactions between users were collected and analyzed to identify influential users. The experimental result is compared to the result from the CELF algorithm with a hypothesis test. It shows that identified influential users from the algorithm and experiment are similar.