摘要
在蓬勃發展的社群網絡上，常出現了眾多意見領袖，帶動他人回應、分享、按讚，進而影響更多人，形成所謂的口碑行銷。然而在廣大的社群平台中，如何找到可有效進行口碑行銷的潛在意見領袖，是一個具挑戰性的問題。我們希望透過文章內容、發文數量、按讚數、留言數、分享數等數值，依據長尾理論（The Long Tail）以及商品特徵找尋特定商品潛在的意見領袖，並進行排名。本研究以Facebook粉絲團為例，開發一個線上視覺化系統，以圖形化介面呈現系統推薦，幫助行銷人員挑選符合需求的粉絲團，並在找尋的過程中掌握商品相關詞彙，對特定商品進行口碑行銷，以達到精準行銷的目的。本系統透過使用實驗，取得使用者回饋，並驗證系統的可用性。從實驗結果顯示，本研究所設計的視覺化分析系統具有幫助找尋潛在意見領袖的功能，並證實了本系統的發展價值。
並列摘要
On the prevailing social media systems, there also exist many opinion leaders whose words can encourage users to respond, share information and click the like button, forming the so-called word-of-mouth marketing. However, since the amount of data on most social networks is huge, how to find potential opinion leaders who can effectively promote word-of-mouth marketing is still a challenging issue. We hope to find the potential opinion leaders of specific products based on characteristics of social network platforms such as the content of articles, the number of posts, the number of likes, the number of comments, and the number of shares, etc. Based on 〞The Long Tail〞 theory and the characteristics of a given product, we hope to find and rank effective opinion leaders. In our research, focusing on the Facebook's fan groups, we have developed an online visualization system to recommend fan groups through graphical interface. We hope to help marketers choose fan groups easily, and collect keywords related to product in the process of finding fan groups. We hope that through these fan groups, Word-of-Mouth can be used to promote specific products for precision marketing. We have conducted user experiments to verify the usability of the system and obtain user feedbacks. The experimental results and user feedbacks reveal that our visualization system indeed can help users find potential opinion leaders for a given product, which confirms the value of developing such a system.