近年來隨著社群網路服務的盛行，臉書已成為現代人最主要的社交工具，許多名人及公司企業也都搶搭著這股風潮，紛紛在臉書上建立起粉絲頁來和粉絲們互動，而在虛擬世界和現實社會之間，兩者所互相造成的影響帶動出許多新興研究議題，透過資訊技術收集虛擬世界裡的資料，能幫助人文學者與社會科學家探索出數位科技與人文社會間的新現象。 本研究針對臉書上的粉絲頁，設計建構出一套臉書資料抓取系統，以協助學者研究分析粉絲頁的動態消息資料，本系統可幫助研究者搜尋出相關粉絲頁，並依照按讚次數排列呈現，協助挑選受歡迎的粉絲頁；讓研究者能抓取特定的粉絲頁資料，抓取到的資料經過解析後分為文章訊息、留言訊息、按讚訊息，並將結果儲存至資料庫；針對已抓取的粉絲頁，自動定時更新至最新資料。 / With the popularity of social networking services in recent years, Facebook has become a major social tool for people. Many celebrities and companies have also gone with the tide to and established a fan page on Facebook to interact with fans. The mutual influence of the virtual world and the real world drives many emerging research agenda. Using information technology to collect data in the virtual world can help the humanities scholars and social scientists to explore new phenomena between digital technology and humanities community. In this thesis, we focus on Facebook fan page data. We design and construct a Facebook fan page crawler to help scholars get data for analysis. The crawler can help researchers find the relevant fan pages along with the numbers of thumbs up and it can help researchers select fan pages. The crawler can help researchers to get the fan page data which they want by extracting post messages, comment messages, and like messages from the data and then storing the results into the database. The crawler also can set update timer to help researchers get the latest information.