由於時代的變遷，資訊量以倍數成長，隨著科技的進步如何有效率的利用資訊技術處理這些大量資料是這幾年被廣泛研究的議題之一。在大量且雜亂的資料中，如何尋找人與人之間的關係並且推測出其中所隱含的資訊，可以透過社會網絡分析對個人或是群體進行觀察。早期的社會網絡分析較著重在靜態網絡分析，亦即不考慮時間因素的情況下所建置的網絡，但現實中人與人之間的關係會隨著時間的改變而有所不同。
本研究希望建置一個政治人物的社交網絡，尋找此社交網絡中隱含的資訊。資料來源以中央選舉委員會提供之選舉公報為主，將每位候選人視為網絡之節點並蒐集候選人的相關資料。一個網絡的建立需要關係作為節點間連結，因此需要將關係作一個明確的定義。最後，根據不同關係建立的網絡，使用社會網絡分析挖掘出有用的資訊。另外可藉由蒐集的資料提供與政治人物相關的查詢。

In recent years, the explosion of data is alarming. How to efficiently process this data to get useful information from it becomes an important issue. At the same time, theory for analyzing large social networks has been developed. It allows us to explore some special individuals, for example, the maximum influential individual in a social network.
In this thesis, we define multiple relationships of Taiwan politicians to construct various social networks. In order to get special individuals in each social network, we use three of the popular indicators to calculate the centrality of the networks. We also implement a system that can show the social networks as well as the query and analysis results from these networks.

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